We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

We are seeking a highly skilled Senior Staff Software Engineer with deep technical expertise in Security and a passion for building secure, reliable, and scalable systems. This role focuses on technical leadership, architecture, and hands-on development to ensure the security and resilience of our core platforms.

You will drive the security, quality, and reliability of backend systems while influencing architecture decisions, mentoring engineers, and partnering with product teams on strategic initiatives.

What You Will Do

• Architect and implement secure, scalable backend systems using Java (Spring Boot) and AWS cloud-native services.
• Lead technical design reviews, enforce security best practices, and ensure system reliability and performance.
• Develop and integrate security features such as authentication, authorization, and identity management (SSO, OIDC, RBAC/ABAC, SCIM).
• Design and implement API security patterns and API authorization at scale for microservices and service mesh environments.
• Embed Generative AI capabilities (e.g., embeddings, RAG, LLM APIs) into product workflows securely and responsibly.
• Write and review code, unblock complex technical challenges, and make critical architectural decisions.
• Champion secure SDLC practices, cryptography standards, and compliance requirements.
• Collaborate with cross-functional teams to define technical roadmaps and deliver mission-critical systems at scale.

Minimum Qualifications

• Bachelor’s degree in Computer Science or related technical field.
• 8 years of professional software development and security engineering experience.
• Proven experience designing and developing large-scale distributed systems.
• Strong knowledge of security architecture

Preferred Qualifications

• Recent hands-on experience (last 3–4 years) building secure, distributed systems at scale, with strong exposure to AI/ML development and hosting in production environments.
• Experience with cloud platforms (AWS, Azure, GCP) for identity, ML infrastructure, and secure deployment.
• Familiarity with Generative AI integration and responsible implementation of LLM-based workflows.
• Exposure to data security principles, including encryption, secure data pipelines, and compliance frameworks.
• Ability to influence technical direction and mentor engineers in security best practices.
• Proven track record of delivering mission-critical, scalable systems in production at enterprise scale.
• Expertise in Java, Spring Boot, and AWS architecture/services (EKS, S3, Lambda, RDS, IAM, KMS).
• 7+ years of solid experience with fundamental algorithms, system design, and large distributed systems.
• Deep experience in cryptography and PKI systems, including certificate management and secure key lifecycle
• 7+ years of coding experience, specifically in Java.
• Strong knowledge of security architecture, authentication/authorization, and cryptographic principles.
• Hands-on experience in building large-scale serving and data infrastructure.
• Experience with service-oriented architecture and web application/services development
• Practical experience in utilizing AWS (Amazon Web Services).
• Experience in designing and constructing machine learning-based applications and systems.
• Experience in leading cross-team system design and execution.

Pay & Benefits   

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation. 

The base pay for this position ranges from $174,00/year to $299,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits  

• Medical/Dental/Vision/Life, AD&D insurance  
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station 

General Description of Other Compensation

 “Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.  

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.
• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.
• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or gender (including pregnancy, gender identity, gender expression, sexual orientation, transgender status), national origin, age, disability, medical condition, HIV/AIDS or Hepatitis C status, marital status, military or veteran status, use of a trained dog guide or service animal, political activities, or affiliations, citizenship, or any other characteristic or class protected by the laws or regulations in the locations where we operate. If you need assistance and/or reasonable accommodation in the recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Requisition ID: R0067878

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Finance & Strategy team is an integral thought partner to Stripe’s core functional leaders.  We bring understanding and predictability to Stripe’s bottom line financials.  We work cross functionally across many surfaces at Stripe and help steward Stripe’s resource investments to improve the durability of our long term financial performance.

What you’ll do

We’re hiring a seasoned finance leader to run Central GTM Finance & Strategy on the GTM F&S team. You will lead global planning, consolidation, metrics & analytics, and strategic initiatives that scale GTM finance operations. This role partners closely with Global Sales leadership to guide go-to-market strategy, improve forecasting accuracy, optimize investments, and accelerate enterprise growth as Stripe expands internationally.

Responsibilities

• Lead and develop a team of eight finance professionals supporting Global Sales; deliver insights across user-level performance, sales productivity, pipeline conversion, quota attainment, and strategic account planning to support recurring business reporting cadences.
• Provide finance leadership for global sales support functions including Solution Architecture, Customer Success, Renewals, and GTM Operations.
• Own global forecasting, planning, and budgeting for Sales; surface actionable insights that inform investment decisions and drive sales efficiency.
• Define and maintain key business metrics and KPIs to monitor health and proactively flag risks and opportunities.
• Use data-driven analysis to diagnose performance, recommend actions to accelerate revenue growth and margins, and optimize investments.
• Partner with Sales, Sales Operations & Strategy, and Marketing to evaluate ROI of GTM initiatives and customer acquisition strategies.
• Build dynamic financial and operating models to assess new sales motions, pricing changes, large enterprise deals, and regional expansion scenarios.
• Work with leadership to create long-range planning models that align team strategy with GTM and company priorities.
• Design, scale, and implement reporting and dashboards that track funnel metrics and primary investment drivers.
• Independently run complex SQL queries and perform hands-on analysis of raw data to validate models, uncover root causes, and produce actionable insights.
• Leverage AI and generative tools to speed analysis, automate repetitive tasks, surface insights, and synthesize recommendations.
• Drive process automation and data streamlining to improve reporting accuracy and decision velocity.
• Contribute to quarterly business reviews and long-range planning with scenario analysis and strategic recommendations.
• Translate complex financial and sales data into clear, concise narratives for executive audiences.

Who you are

You’re an analytical, execution-oriented finance leader with strong business acumen and a passion for GTM strategy. You thrive in fast-moving, ambiguous environments and balance strategic thinking with hands-on work. If you want to help Stripe scale its enterprise footprint and drive decisions through data, we want to hear from you.

Minimum requirements

• 10+ years in FP&A, Strategic Finance, or GTM Finance supporting enterprise sales teams.
• Proven ability to analyze pipeline health, forecast revenue, and model user and sales dynamics in complex B2B settings.
• Track record of partnering with senior GTM leaders and influencing decisions through financial insight.
• Strong financial modeling experience and familiarity with large, multi-variable planning tools.
• Proficiency in SQL to independently query and manipulate complex datasets.
• Analytical fluency at scale; comfortable working directly with large, complex datasets (not just financial models) to independently validate outputs, diagnose root causes, and drive conclusions in close partnership with Engineering, Data Science, and Analytics teams. 
• Ability to navigate ambiguous, evolving data environments; experience identifying non-obvious data pitfalls, understanding how data flows across systems, and building reliable analyses in settings where infrastructure and tooling are still maturing. 
• Minimum 3 years of people management experience with success leading high-performing finance teams.
• Excellent communication and presentation skills; ability to distill complex concepts into clear, actionable insights.
• Comfortable operating in fast-paced, ambiguous environments; able to balance strategy with tactical execution.

Preferred qualifications

• Experience working at a high-growth technology or financial services company
• Anaplan, Tableau or other equivalent application experience
• Advanced SQL skills
• Experience in data visualization and dashboarding

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities.

In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models.

You will:

• Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities.
• Design and experiment new approaches to preference optimization.
• Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
• Publish research findings in top-tier AI conferences.

Ideally you’d have:

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
• Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
• Excellent written and verbal communication skills

• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

About the General Agents Team

The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers.

About the Role

As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

You will:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideally you’d have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves:

• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About the ACE team 

The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. 

About This Role

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Ideally you’d have: 

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally. 

Nice to have:

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax. 
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH 
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an Applied AI Engineer, you’ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins. Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you’ll use to improve your product’s performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

• Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions 
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.
• Be able and willing to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As a Staff Machine Learning Research Scientist on the LLM Evals team, you will lead the development of novel evaluation methodologies, metrics, and benchmarks to measure the capabilities and limitations of frontier LLMs. You will help define what "good" looks like in generative AI, driving research that informs both our internal roadmap and the broader research community. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs.

You will:

• Drive research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Mentor and guide research scientists and engineers, providing technical leadership across cross-functional projects.
• Stay deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience tech leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As the Tech Lead Manager of the LLM Evals Research team, you will lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs. 

You will:

• Lead a team of highly effective research scientists and research engineers on LLM evals.
• Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Remain up-to-date on ongoing research in the team, help work through technical challenges, and be involved in design decisions
• Remain deeply involved in the research community, both understanding trends, and setting them
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience supporting and leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications.

As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.

As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.

You will:

• Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).  
• Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.
• Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.
• Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.
• Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.
• Stay deeply connected to the research community, understanding major trends, and helping set them.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.
• A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.
• Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations.

About This Role

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale’s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Ideally, you’d have:

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes.

• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.).

• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning.

• Strong written and verbal communication skills, along with the ability to work effectively across teams.

Nice to have:

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX.

• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents.

• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar.

• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH.

• Proficiency in cloud-based ML development, with experience in AWS or GCP environments.

Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments.

Voyager is an innovative defense, national security and space technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space. 

Forge the Future: Join Voyager Technologies 

The future belongs to those who build it. At Voyager Technologies, we’re building technologies that protect lives, expand frontiers and prepare us for what’s next. And we’re doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart.  

You’ll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We’re a company of doers, thinkers and builders, united by purpose and grounded in reality. 

If you want to put your skills to work where the stakes are real and the mission is bigger than any one person, forge the future with Voyager. 

____________________________________________________________________________________ 

Job Summary: 

We are seeking a Principal Technical Director, AI-Enabled Spectrum Dominance to serve as the senior technical leader for our advanced RF systems, software, algorithms, and agentic AI portfolio as applied to space-based and terrestrial electromagnetic warfare and sensing. In this pivotal role, you will drive the technical vision for the future of spectrum dominance while simultaneously leading the application of Voyager’s Agentic Computational Engineering (ACE) platform to RF hardware systems and digital signal processing (DSP) development.

This role uniquely combines deep RF domain expertise with leadership over AI-driven hardware design and simulation workflows. You will oversee how agentic AI systems are deployed to compress RF hardware development cycles—from antenna design and transceiver architecture to DSP algorithm development and system-level integration—accelerating the path from concept to deployable, mission-critical capability for the warfighter.

The right person has deep familiarity with hardware, software, and algorithms across a variety of RF functions, including communications, electronic warfare (EW), radar, and sensing, with particular emphasis on space-based active and passive RF systems. You must be as comfortable defining and executing complex research and development programs as you are productizing outcomes into monetizable commercial motions. You must also have the vision and technical fluency to direct how multi-agent AI platforms transform traditional RF engineering workflows.

You will be joining the Advanced Technology Development team, a specialized unit within our Strategic Growth and Technology Organization. This team is responsible for defining and developing Voyager’s future technologies, with a relentless focus on high-impact, high-ROI technology and product R&D. You will work at the intersection of Voyager’s Spectrum Dominance portfolio and the Agentic Computational Engineering (ACE) team—the group building Voyager’s Generative Engine, the AI-native platform that compresses complex hardware development cycles from years to days.

You will be joining the Advanced Technology Development team, a specialized unit within our Strategic Growth and Technology Organization. This team is responsible for defining and developing Voyager's future technologies, with a relentless focus on high-impact, high-ROI technology and product research and development. Our technology portfolio spans the totality of Voyager's capabilities and beyond—we are tasked with creating both leap-ahead capabilities in existing technology areas and strategically moving into and developing foundational technology in new, uncharted areas.

Responsibilities:  

• Technical Leadership & Vision

  • Define and drive the technical roadmap for Voyager’s Spectrum Dominance portfolio, serving as the ultimate technical authority for RF, EW, radar, and sensing programs—with specific emphasis on space-based active and passive RF systems.
  • Set the strategic direction for applying Agentic Computational Engineering to RF hardware design, DSP algorithm development, and end-to-end RF system integration.
  • Own the vision for how AI agents are used across the RF hardware design lifecycle, from generative antenna and front-end design through automated DSP algorithm synthesis and simulation-in-the-loop optimization.

  Agentic Computational Engineering for RF & DSP

  • Lead and oversee the deployment of Voyager’s ACE platform (the Generative Engine) for RF-specific applications, ensuring AI agents can autonomously design, simulate, evaluate, and optimize RF hardware and DSP subsystems.
  • Direct the development of domain-specific AI agents for RF engineering workflows—including agents for electromagnetic simulation, transceiver architecture exploration, waveform design, interference analysis, and signal chain optimization.
  • Partner with the ACE platform team to define requirements for agent orchestration, physics simulation integration (EM solvers, thermal analysis, signal integrity), and design-for-manufacturing constraints specific to space-qualified RF hardware.
  • Establish automated simulation loops between RF/DSP design agents and high-fidelity physics solvers, including meshing, solving, and post-processing for antenna patterns, RCS analysis, link budgets, and spectral performance.
  • Drive adoption of AI-first workflows across the RF engineering organization, championing use of LLM-based tools and agents to accelerate documentation, design review, test planning, and compliance verification.

  R&D Execution

  • Lead the execution of complex, high-stakes research and development programs for next-generation space-based and terrestrial RF systems, ensuring technical risks are managed and innovative solutions are delivered on schedule.
  • Oversee the design, analysis, and testing of advanced RF systems including satellite communications payloads, space-based SIGINT/ELINT collectors, synthetic aperture radar (SAR), and passive RF sensing architectures.

  End-to-End System Architecture

  • Architect complete RF systems bridging DSP algorithms, software-defined radio (SDR) hardware, FPGA/SoC platforms, and high-level mission software, ensuring seamless integration across the entire signal chain for both space and ground segments.
  • Define system architectures for space-based RF payloads that account for the unique constraints of the orbital environment: radiation tolerance, thermal management, power budgets, size/weight limitations, and long-duration mission reliability.

  Productization & Commercialization

  • Bridge the “valley of death” by guiding technologies from TRL 3–6 research efforts into robust, productized solutions ready for manufacturing and deployment. Work closely with product and business teams to define commercialization strategies.
  • Leverage agentic AI capabilities to accelerate productization timelines, using the Generative Engine to rapidly iterate on design variants and manufacturing-ready configurations.

  Team Building & Mentorship

  • Build and inspire a world-class engineering team spanning RF hardware, DSP, and AI-enabled design disciplines. Mentor senior engineers and researchers, fostering a culture of technical rigor, creativity, and rapid iteration.
  • Grow and lead a multidisciplinary team that includes RF engineers, DSP developers, and AI/ML engineers working collaboratively on agentic RF design capabilities.

  Cross-Functional Collaboration

  • Partner with business development and capture teams to shape new opportunities, providing technical grounding to win major government contracts.
  • Collaborate with the ACE platform team, propulsion, electronics, and manufacturing domain teams to ensure RF-specific agentic capabilities integrate seamlessly with Voyager’s broader Generative Engine ecosystem.

Required Qualifications:  

• Bachelor’s degree in Electrical Engineering, Physics, Mathematics, or a related field.
• Must be eligible to obtain and maintain a US Government clearance (requires US citizenship).
• Space-Based RF Systems Expertise: Demonstrated background in the design, development, and deployment of space-based active RF systems (such as satellite communications transponders, SAR payloads, space-based radar, or active phased arrays for orbital platforms) and/or passive RF systems (such as space-based SIGINT/ELINT collectors, radiometers, or passive sensing payloads). Must have direct experience with the unique constraints of the space environment, including radiation hardening, thermal management, power budgeting, and long-duration reliability.
• Deep RF & Systems Expertise: Proven background in designing and developing complete end-to-end RF systems (both RF front-ends and digital subsystems). Deep understanding of the physics of the spectrum and the hardware required to dominate it across communications, EW, radar, and sensing domains.
• SDR Proficiency: Extensive experience designing and developing complex software-defined radio (SDR) systems, including familiarity with modern transceiver architectures and FPGA/SoC platforms.
• Algorithm Development: Strong track record in designing and developing complex digital signal processing (DSP) and RF Machine Learning (RFML) algorithms. Understands how to apply modern compute—including AI/ML techniques—to solve traditional RF problems.
• R&D Leadership: Demonstrated experience leading multi-disciplinary engineering teams (Hardware, Software, RF, FPGA, AI/ML) through the full lifecycle of advanced R&D programs, from white paper to prototype to deployment.
• Domain Expertise: Demonstrated background fielding capability in one or more of the relevant spectrum dominance domains: SIGINT, EW, or Radar, with preference for space-based applications.
• Programmatic Execution: Familiarity with the unique challenges of government R&D contracting, including experience delivering against technical milestones for customers like DARPA, ONR, AFRL, NRO, or the Space Force.
• Proposal Development: Proven proposal development experience, including contributing to technical volumes and cost estimations for complex government solicitations.

Preferred Qualifications:  

• Master’s or PhD in Electrical Engineering, Physics, Mathematics, or a related field.
• Active U.S. Top Secret / SCI Security Clearance.
• Direct experience with space-based RF payload programs (design, integration, test, and on-orbit operations) for DoD or Intelligence Community customers.
• Experience with or strong interest in AI-driven engineering workflows, including agentic AI systems, LLM-based design tools, automated simulation frameworks, or generative design platforms.
• Familiarity with agent orchestration frameworks (e.g., LangGraph, AutoGen, or custom agent runtimes) and an understanding of how multi-agent systems can be applied to hardware design problems.
• Experience with electromagnetic simulation tools (HFSS, CST, FEKO, or equivalent) and a vision for how AI agents can automate and accelerate simulation-driven RF design.
• Experience productizing advanced R&D into monetizable commercial motions, demonstrating a track record of turning science projects into shipping products.
• Demonstrated history of leading winning proposals for space-based RF programs.
• Background in orbit-specific RF considerations: Doppler compensation, atmospheric propagation effects, space-to-ground link budgets, anti-jam architectures, and low-probability-of-intercept (LPI) waveforms.
• Willingness to travel up to 25% to customer sites, test ranges, and Voyager locations.

Please click “Apply” to submit your application. 

Voyager offers a comprehensive, total compensation package, which includes competitive salary, a discretionary annual bonus plan, paid time off (PTO), a comprehensive health benefit package, retirement savings, wellness program, and various other benefits. When you join our team, you’re not just an employee; you become part of a dynamic community dedicated to innovation and excellence.

Voyager is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.  

Minority/Female/Disabled/Veteran 

The statements contained in this job description are intended to describe the general content and requirements for performance of this job. It is not intended to be an exhaustive list of all job duties, responsibilities, and requirements. This job description is not an employment agreement or contract. Management has the exclusive right to alter the scope of work within the framework of this job description at any time without prior notice. 

Voyager is an innovative space, defense, and national security technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space. 

Forge the Future: Join Voyager Technologies 

The future belongs to those who build it. At Voyager Technologies, we’re building technologies that protect lives, expand frontiers and prepare us for what’s next. And we’re doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart.  

You’ll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We’re a company of doers, thinkers and builders, united by purpose and grounded in reality. 

If you want to put your skills to work where the stakes are real and the mission is bigger than any one person, forge the future with Voyager. 

We are seeking a Principal Electrical Engineer to lead PCB design within the Agentic Computational Engineering (ACE) platform team and to encode the realities of space-electronics PCB design and manufacturing directly into our generative engine. In this role, you will own end-to-end PCB design — schematic capture, stackup definition, high-speed and mixed-signal layout, signal and power integrity, fabrication and assembly readiness — for flight hardware, and translate that hard-won expertise into the constraints, heuristics, and feedback loops that let our AI agents design boards that can actually be built, qualified, and flown.

You will work at the intersection of PCB design, space-grade manufacturing, and AI — pairing your own hands-on board work with software development that captures DfM, DfA, and DfT considerations as code. This role is ideal for someone who has personally laid out flight boards, knows what fabricators and assembly houses actually need to see on a drawing package, and is excited to guide the team and write the software that lets an agent reason about those same trade-offs. You should be passionate about both leading a team and building this product: not just designing one more board, but multiplying your impact by encoding your judgment into a system that designs the next thousand.

You will be joining the Agentic Computational Engineering (ACE) team, a specialized group within our Advanced Technology Development organization. ACE is responsible for building Voyager’s Generative Engine – the AI-native platform that compresses complex hardware development cycles from years to days. We design agentic AI systems that pair deeply with physics simulation, test data, and modern manufacturing so that Design for Manufacturing (DfM), Design for Assembly (DfA), and Design for Test (DfT) are built into the very first line of code and the very first sketch of a design.

The position reports to the VP, AI & Autonomy and is part of the Technology and Advanced Development department based in Los Angeles, CA; Washington D.C; Seattle, WA.

This role is hybrid based in Los Angeles, CA; Washington D.C; Seattle, WA.

• Own the vision and execution of the PCB vertical of the Agentic Computational Engineering platform — defining how an agentic system should reason about end-to-end PCB design and manufacturing for space-grade flight electronics, and guiding the engineering team that implements it.
• Frame the problem space for the team: catalogue the design and manufacturing decisions a senior PCB engineer makes on a flight program (substrate and stackup, SI/PI, DfM/DfA/DfT, parts derating, fab and assembly liaison, qualification) and translate each into structured problems an agent can solve autonomously.
• Plan the PCB vertical's roadmap in lockstep with AI, simulation, manufacturing, and product leadership — sequencing capabilities, identifying high-leverage bets, and articulating clear success criteria for each agentic capability we ship.
• Educate the team continuously on space-electronics PCB design and manufacturing — running design-review walkthroughs, writing internal references, and turning your judgment into shared mental models the rest of the team can build against.
• Drive product taste for the PCB vertical: define what a great agent-generated design package looks like, what quality bar it must hit, and where the agent should defer to a human — so the team builds something that practicing PCB engineers actually trust.
• Lead testing and qualification of agent-generated designs — running design reviews, fabricating and assembling representative boards, and executing electrical, environmental (vibe, thermal, EMI/EMC), and radiation campaigns to evaluate real-world performance.
• Provide detailed, structured feedback to the team building the platform — turning every test, fab spin, and design review into specific, actionable signals that improve the agents, the constraint models, and the simulation tie-ins.
• Partner with fab houses, assembly houses, and component vendors to encode their real constraints — IPC class 3, NASA workmanship, lead times, parts availability, qualification artifacts — into the platform so generated designs are buildable on the first spin.
• Set the technical direction for AI-driven tooling in the PCB vertical (Python/C++ services, LLM-based agents, scripting), guiding engineers on how to decompose PCB-engineering judgment into agents that can make decisions autonomously and explain them.
• Represent the PCB vertical to Voyager hardware programs and external customers — communicating capabilities, limitations, and the roadmap with the credibility that comes from having designed flight hardware yourself.

In this role, the essential functions are:

If your experience aligns with our basic qualifications and you are inspired by our mission, we’d like to connect. If you don’t see the right role right now, Join Our Talent Community and stay connected as we continue to build what’s next. 

• 12+ years of hands-on PCB design experience for space, aerospace, defense, or other high-reliability electronics, including delivered flight or flight-equivalent hardware on programs you can speak to in depth.
• Demonstrated technical leadership of a PCB or hardware function — setting direction, mentoring engineers, owning quality, and being the person the rest of the team escalates to on hard design and manufacturing calls.
• End-to-end mastery of the PCB process — schematic capture, multi-layer stackup design, controlled-impedance and high-speed routing, mixed-signal and RF layout, SI/PI analysis, DfM/DfA/DfT, fab/assembly liaison, bring-up, and environmental/qualification testing — in Altium Designer or equivalent ECAD.
• Excellent product taste: a track record of deciding what to build, what quality bar to hold, and what to cut — and articulating those calls clearly to engineering, product, and program stakeholders.
• Strong communication and teaching ability — comfortable running design reviews, writing internal documentation, and educating non-PCB engineers (AI, software, simulation, manufacturing) on what matters and why.
• Strong programming skills in Python and/or C++, and demonstrated use of AI tools, LLMs, or scripting to automate engineering work — design reviews, BOM management, layout checks, parts-stress analysis, or data pipelines.
• Ability to define how an agentic system should reason about engineering problems — decomposing PCB design and manufacturing decisions into objectives, constraints, and feedback signals an autonomous agent can act on.
• Genuine passion for building this product: excited to lead a team that turns your hard-won PCB judgment into a generative engine designing the next thousand boards.
• Ability to obtain and maintain a U.S. Top Secret Security Clearance.

Preferred Qualifications: 

• Master's or PhD in Electrical Engineering or related discipline.
• Experience leading PCB design or hardware engineering at NASA centers, JPL, major space primes, or new-space companies; familiarity with PDR/CDR processes, NASA workmanship standards (NASA-STD-8739), SMC-S-016, MIL-STD-461G, WCCA/EPSA, and IPC class 3.
• Hands-on experience with FPGA/SoC-based single-board computers (e.g., Xilinx Ultrascale+ MPSoC, GR712, RTAX/RTG4), high-speed ADC/DAC layout, and RF front-ends across UHF through Ka-band.
• Experience defining or qualifying substrates and stackups (e.g., Rogers, Isola Tachyon/MT-40) against electrical, thermal, and radiation-environment requirements, and running radiation effects testing (TID, SEE, SEL, SEU).
• Familiarity with systems-engineering tooling (JAMA, DOORS, Jira) and EICD/requirements practices spanning box, slice, and board level.
• Track record of building or leading the build of internal tooling, design automation, or AI/LLM-based assistants that measurably improved PCB design or review throughput.
• Experience guiding software or AI engineers — translating engineering domain knowledge into specifications, evaluation criteria, and feedback that shape what gets built.
• Evidence of personal projects in electronics, robotics, or RF — the kind of work where you build the thing yourself for the love of it.

The good faith base salary range for this role is$225,000 - $290,000 at the time of this posting. Where you fall within the range depends on your experience, skills, and location. This range reflects base salary only and does not include benefits or bonus/incentive. This range may be adjusted in the future.

This position is incentive plan eligible.

Voyager offers a highly competitive total compensation package designed to support the well-being, growth, and success of our employees. Employees benefit from a flexible and comprehensive rewards program that supports both professional and personal well-being.  

• Flexible Time Off (FTO), empowering employees to take the time they need to recharge and maintain a healthy work-life balance

• Comprehensive medical, dental, and vision coverage for employees and their families, with a significant portion of premiums covered by the company and many benefits paid at 100% for employees
• Flexible, affordable gym memberships with 12,700+ options nationwide including 24 Hour Fitness, EoS Fitness, Crunch Fitness, Anytime Fitness, Blink Fitness, Chuze Fitness and more! No long-term contracts and FREE on-demand workout videos before you enroll

• 401(k) retirement plan with a 50% company match on contributions up to 8%, supporting long-term financial security

• Company wellness programs that support physical and mental well-being

• Additional voluntary benefits and employee support resources
• The opportunity to work alongside a highly talented team in an innovative, mission driven environment

Voyager is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. 

Able to obtain and maintain a U.S. security clearance

Minority/Female/Disabled/Veteran 

The statements contained in this job description are intended to describe the general content and requirements for performance of this job. It is not intended to be an exhaustive list of all job duties, responsibilities, and requirements. This job description is not an employment agreement or contract. Management has the exclusive right to alter the scope of work within the framework of this job description at any time without prior notice. 

We are seeking an innovative, customer-focused leader to drive the AI Platform product area at Talkdesk. As the Principal Product Manager, you will be at the helm of shaping a platform that powers AI-driven solutions for the future of customer engagement. You will collaborate with designers, engineers, GTM teams, and the executive leadership to build cutting-edge AI capabilities that accelerate growth and lead to market leadership.

In this role, you will oversee a mix of strategic product leadership and people management, with the opportunity to guide both product innovation and team development. As a key partner to our GTM teams, you’ll serve as the face of the AI platform, engaging with customers, prospects, and partners to drive adoption and success.

Job Summary:

• The Principal Product Manager is responsible for leading the development and management of complex products from ideation to launch. This includes defining product strategy, conducting market research, developing product roadmaps, and collaborating with cross-functional teams to ensure successful product launches. The Principal Product Manager is a senior leader who provides guidance and direction to other product managers and technical staff.

Duties and Responsibilities:

• Lead the development and management of complex products, from ideation to launch, ensuring they are completed on time, within budget, and meet quality standards
• Work closely with cross-functional teams, including engineering, design, sales, and marketing, to ensure that all aspects of the product are aligned
• Develop and maintain product roadmaps and feature backlogs, and track progress against milestones
• Conduct market research and gather customer feedback to identify customer needs and pain points, and use this information to inform product decisions
• Develop and maintain strong relationships with customers and other key stakeholders, in order to identify critical use cases that can be solved by AI solutions and gather feedback to improve product capabilities and inform future launches
• Use data and metrics to measure the effectiveness of products and features, and make data-driven decisions to optimize product performance
• Manage the product lifecycle, from launch to end-of-life, ensuring that products are updated and maintained as needed
• Provide leadership and guidance to other product managers and technical staff, ensuring they have the resources and support needed to complete their work
• Manage relationships with suppliers, vendors, and contractors to ensure that products are developed and delivered on time and within budget
• Ensure that all product work is completed in compliance with industry regulations and standards.

Qualifications:

• Bachelor's degree in Business, Marketing, Engineering, or a related field
• At least 5 years of experience in product management, with a proven track record of successfully launching and managing complex products
• Strong leadership and product management skills, with the ability to manage and motivate a team of product managers and technical staff
• Strong analytical skills, with the ability to use data and metrics to make informed product decisions
• Experience in developing product strategy and roadmaps, with a deep understanding of customer needs, market trends, and competitive landscape
• Excellent communication skills, with the ability to effectively communicate product strategy and vision to cross-functional teams and senior leadership
• Experience working in an agile development environment, with a strong understanding of agile methodologies
• Proven experience managing a portfolio of AI driven products, with a strong ability to prioritize features, models, and experiments across multiple products simultaneously.
• Understand and be able to explain with detail the concepts of AI, generative AI, Agentic AI and underlining technologies (LLMs, prompts, vectors, among others).
• Strong understanding of industry regulations and standards with exposure to and knowledge of AI technologies

Pay Range (Base Pay):   $115,000 - $273,000

Other Types of Pay: Based on level and role the employee may be eligible for long term incentives in the form of equity and short term incentives of either bonus or commission. 

Health Insurance: Medical, Dental, Vision, Life and Disability Insurance, Employee Assistance Program (EAP).

Retirement Benefits: 401(k) plan

Paid Time Off: Talkdesk offers an uncapped paid time off program for exempt employees and an accrual-based program for non-exempt employees; both are subject to manager approval and consistent with business needs.

Paid Holidays: Talkdesk offers 14 paid holidays each year. 

Paid Sick Leave: Exempt employees have uncapped paid time off and non-exempt sick leave follows accrual standards; both are subject to manager approval and consistent with business needs.

Method of Application: Apply online.

Application Window: The application window is expected to close at least 7 days from the posting date. The application was posted on 5/1/2026.

Benefits and perks listed above may vary based on the nature of your employment with Talkdesk.

All questions or concerns about this posting should be directed to the Talent team at Talent@talkdesk.com.

About Us

Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.

We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X,  and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.

About the Role

We are looking for an experienced Legal Program Manager to join Twitch's close-knit legal team. Reporting to the General Counsel, the Legal Program Manager will support the team to plan, prioritize, and achieve complex deliverables on initiatives with a regulatory or legal touchpoint. You will also play a key role in the Legal Department’s continuing identification and deployment of AI-driven systems in our work.

You can work from San Francisco, CA; Seattle, WA; Irvine, CA; Culver City, CA or New York, NY.

You Will:

• Own the intake, planning, coordination, and tracking of legal compliance initiatives from initial request through completion.
• Serve as the primary architect of AI-powered solutions and be responsible for driving effective adoption of AI-enabled legal solutions within the legal team.
• Serve as connective tissue between Legal and key partners in Product Development and Operations.
• Partner with attorneys, subject matter experts, and cross-functional stakeholders to define scope, clarify requirements, establish timelines, and drive work forward.
• Translate legal and compliance recommendations into user stories, and create clear, actionable workstreams with defined owners, milestones, dependencies, and risk considerations.
• Facilitate stakeholder meetings to iterate on solutions, drive alignment, resolve blockers, and ensure timely progress on key initiatives.
• Monitor and report on the status of legal and compliance initiatives, including progress against milestones, outstanding risks, and escalation needs.
• Maintain Jira dashboards to support visibility, accountability, and reporting.
• Develop, refine, and scale frameworks, processes, and documentation that improve how Legal manages programs, compliance recommendations, and cross-functional execution.

You Have:

• 6+ years experience in a project or program management role
• 5+ years leading project planning efforts.
• Experience leading technology adoption, change management, or process automation initiatives within a legal, compliance, or operations environment
• Familiarity with Google Docs, Jira, ServiceNow, and Salesforce
• Strong organization, communication and collaboration skills
• PMP preferred

Bonus Points

• 2+ years as a people manager or demonstrated experience mentoring, leading or developing others
• Hands-on experience evaluating, piloting, or deploying AI-powered tools (e.g., contract review platforms, generative AI assistants, legal workflow automation) or familiarity with prompt engineering and AI-assisted workflows

Perks

• Medical, Dental, Vision & Disability Insurance
• 401(k)
• Maternity & Parental Leave
• Flexible PTO
• Amazon Employee Discount

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 

Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 

Job ID: TW9176

Position Overview

Xaira is seeking enthusiastic and motivated candidates to join our team! As an AI Scientist, you will have prior experience in developing and implementing new deep learning methods while upholding a track record of AI Innovation demonstrated through publications in Artificial Intelligence/Machine Learning or projects applying them to interdisciplinary fields. You will be a crucial member of our core AI team, comprising highly creative and talented peers who are all experts in developing state of the art AI models. With your team, you will initiate and drive new projects that advance the SOTA AI models for biology impacting drug discovery and clinical development. You will also have the chance to work closely with interdisciplinary experts with world-class biology, drug discovery, and clinical expertiseWe welcome candidates with diverse backgrounds and experiences. We welcome candidates across the spectrum of experience. Teams thrive when they are diverse (across all axes), and we encourage all eligible applicants to apply.

The role is open to the following locations: San Francisco Bay Area, Seattle and London.

Key Responsibilities

• Completed (or within one year of completing) a PhD in an AI or AI-adjacent field.
• Excited to work, learn and teach within a collaborative team working on challenging problems.

Desirable

Below is a list of qualities/experiences that align with the kinds of things that we are looking for. Please do not read this as an extension of the “requirements” section! We recognise that experiences, opportunities and life-paths vary.

• Publications in journals or ML conferences.
• Public codebases or contribution to public GitHub repositories.
• Industry experience in an AI company, such as an internship or full-time position.
• Knowledge or experience in BioAI.
• Experience building and training neural networks.
• Experience training models across multiple GPUs.

If you are a motivated individual with a passion for applying AI to advance drug discovery and improve human health, we encourage you to apply and join us in our mission to make a positive difference in the world.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $120,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
We are seeking an experienced research engineer to join our team. As a critical member of our interdisciplinary group, you will collaborate closely with AI scientists, engineers, and drug discovery experts to develop and deploy AI models that accelerate the identification and development of novel therapeutics. This role offers the opportunity to apply cutting-edge AI techniques in production settings to address pressing challenges in healthcare and contribute to improving human health globally.

We are particularly interested in candidates who have demonstrated experience building and delivering machine learning systems in industry environments, where rigor, scalability, and cross-functional collaboration are essential. The ideal candidate has experience translating research ideas into robust, production-ready solutions that drive measurable impact.

The role is open to the following locations: San Francisco Bay Area, Seattle

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related fields; advanced degree preferred
• Minimum of five years of industry experience in AI, machine learning, or related roles, with a track record of implementing, scaling, and deploying AI models in production environments.
• Expertise with modern deep learning toolchains and experience with large scale model training.
• Strong understanding of deep learning fundamentals.
• Excellent problem-solving skills, with a keen eye for detail and a passion for tackling complex challenges in the life sciences.
• Effective communication and collaboration abilities, with the capacity to work effectively in a fast-paced, multidisciplinary team environment.
• Publication track record at conferences such as NeurIPS, ICML, or ICLR is a plus, though demonstrated industry impact is prioritized
• If you are a motivated individual with a passion for applying AI to advance drug discovery and improve human health, we encourage you to apply!

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

The Problems You'll Solve

At Carta, our employees set out on a mission to unlock the power of equity ownership for more people in more places. We believe that the problems we solve today unlock the opportunities of tomorrow. Ink is Carta’s Design System – the underlying foundation for how all of Carta looks and feels. Our focus is to make Financial Technology safe, intuitive, performant, and fun (yes, we said that).

As a Senior Design Systems Engineer, you’ll work to: 

• Architect and evolve the Ink component library: You will build and maintain robust, production-ready React components that blend rigorous design system standards, intuitive developer ergonomics, and extensible API design.
• Redefine the Design System for the Agentic Age: You will lead the R&D on how our design system evolves to support AI-driven interfaces. You will update our definition of a design system to accommodate generative workflows, ensuring Ink is optimized for both human developers and AI agents.
• Bridge the gap between design and code: You will act as a technical translator, taking concepts from Figma and turning them into performant UI code, ensuring that the "polish" of the design is never lost in translation.
• Elevate frontend quality and developer velocity: You will drive cross-functional projects to improve animation fluidity, CSS architecture, and system modularity, helping product teams solve 80% of their UI problems instantly so they can focus on the unique 20%.
• Coach and advocate for system adoption: You will mentor engineers and designers across the organization, conducting code reviews and design reviews to ensure best practices are met, while gathering feedback to iteratively improve the system’s flexibility and ease of use.

The Team You'll Work With

You’ll be joining our Design System team “Ink”. Ink is where visual design, user experience best practices, and modern React architecture fuse together to create a beautiful set of tools that allow teams to create great products fast. Our ultimate purpose is to enable great design at scale. We are a team that sits at the intersection of design and engineering; we build the foundational components, tooling, and documentation that empower hundreds of Carta engineers and designers to ship consistent, high-quality, and accessible interfaces.

About You

We are seeking an opinionated but humble builder who cares deeply about the craft of software and the details of design. You have likely built or maintained a component library before and understand the unique challenges of serving other developers as your primary customers.

• 7+ years of relevant experience recommended: Specifically in frontend engineering with a strong focus on design systems, AI-assisted development, or UI infrastructure.
• AI-Forward Innovator: You are actively pushing the limits of what design systems can do with AI. You are eager to explore how component APIs, tokens, and documentation can be optimized to support AI development patterns and the future of agentic UI.
• Systematic Thinker: You have a track record of replacing custom, one-off UI with modular, reusable solutions, and you can articulate the trade-offs of API design decisions to both engineers and designers.
• React & CSS Expert: You possess deep, expert-level knowledge of React (modern patterns, hooks, context), CSS (architecture, scalability), and animation technologies  such as CSS Animations, Framer, and D3. You write code that is not just functional, but a joy for other developers to use.
• Design Fluent: You are comfortable working and collaborating  inside Figma. You understand the nuances of interaction design and can prototype complex UI behaviors to validate concepts before they reach production.
• Champion of Quality: You have a "polish-oriented" mindset. You sweat the details on accessibility, performance, and visual fidelity, ensuring that our system sets a high bar for the rest of the company.

Salary

Carta’s compensation package includes a market competitive salary, equity for all full time roles, exceptional benefits, and, for applicable roles, commissions plans. Our expected cash compensation (salary + commission if applicable) range for this role is: 

• $212,500 - $250,000 in San Francisco, CA; New York, NY
• $201,000 - $237,500 in Seattle, WA

We are hiring for multiple levels and locations, so final offers may vary from the amounts listed based on geography, experience and expertise, and other factors.

We are seeking a Generative AI Chief Engineer Lead to drive innovations in autonomous vehicle technology using deep learning and reinforcement learning. In this dynamic role, you will design state-of-the-art algorithms and systems that enable safe, efficient, and intelligent autonomous capabilities. Today, employing mass quantities of autonomous robots requires heavy human oversight and execution. Anduril is leveraging AI approaches to improve effectiveness of autonomous missions, offload operator burden, and speed up execution via realtime monitoring, recommendations to users, and multi-modal interaction patterns. You will apply proven and un-proven approaches to create prototypes for expanding the capability of autonomous systems.

What You’ll Do

• Develop Advanced Agentic Software - Design and implement novel agent-based software systems to improve sensor perception, prediction, and decision-making for autonomous vehicles
• Apply Agentic Reasoning - Design and implement integrated agents and AI models to solve for end-user autonomous systems workflows.
• End-to-End System Integration - Collaborate with cross-functional teams to integrate research prototypes into robust, production-ready systems including simulation environments and real-world platforms.
• Research & Experimentation - Conduct research into reinforcement learning strategies and deep architectures, iterate on experimental designs, and evaluate performance using rigorous quantitative metrics.
• Data-Driven Innovation - Utilize real-world and synthetic data to enhance model robustness and generalization, leveraging scalable training pipelines on distributed systems.

Required Qualifications

• Sophisticated knowledge of LLM's with an understanding of how they work and how they're applied
• Solid experience with reinforcement learning methods and their application to autonomous systems.
• Proven experience of shipping products end to end
• Experience with simulation or real-world validation for autonomous vehicles is highly desirable.
• A degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Eligible to obtain and maintain an active U.S. Top Secret security clearance
• Travel up to 40+% of time to build, test, and deploy capabilities in the real world

Preferred Qualifications

• PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community.
• Proven experience in deep learning research and development, particularly in generative AI. This includes diffusion models and autoregressive generative models.
• Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar).
• Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines.
• Strong programming skills in Python and familiarity with C/C++ is a plus.
• General software engineering experience solving motion planning or related robotics problems.

We are seeking a AI Chief Engineering Lead to drive innovations in autonomous vehicle technology using deep learning and reinforcement learning. In this dynamic role, you will design state-of-the-art algorithms and systems that enable safe, efficient, and intelligent autonomous capabilities. Today, employing mass quantities of autonomous robots requires heavy human oversight and execution. Anduril is leveraging AI approaches to improve effectiveness of autonomous missions, offload operator burden, and speed up execution via realtime monitoring, recommendations to users, and multi-modal interaction patterns. You will apply proven and un-proven approaches to create prototypes for expanding the capability of autonomous systems.

What You’ll Do

• Develop Advanced Agentic Software - Design and implement novel agent-based software systems to improve sensor perception, prediction, and decision-making for autonomous vehicles
• Apply Agentic Reasoning - Design and implement integrated agents and AI models to solve for end-user autonomous systems workflows.
• End-to-End System Integration - Collaborate with cross-functional teams to integrate research prototypes into robust, production-ready systems including simulation environments and real-world platforms.
• Research & Experimentation - Conduct research into reinforcement learning strategies and deep architectures, iterate on experimental designs, and evaluate performance using rigorous quantitative metrics.
• Data-Driven Innovation - Utilize real-world and synthetic data to enhance model robustness and generalization, leveraging scalable training pipelines on distributed systems.

Required Qualifications

• Sophisticated knowledge of LLM's with an understanding of how they work and how they're applied
• Solid experience with reinforcement learning methods and their application to autonomous systems.
• Proven experience of shipping products end to end
• Experience with simulation or real-world validation for autonomous vehicles is highly desirable.
• A degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Eligible to obtain and maintain an active U.S. Top Secret security clearance
• Travel up to 40+% of time to build, test, and deploy capabilities in the real world

Preferred Qualifications

• PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community.
• Proven experience in deep learning research and development, particularly in generative AI. This includes diffusion models and autoregressive generative models.
• Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar).
• Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines.
• Strong programming skills in Python and familiarity with C/C++ is a plus.

About Us:

Grow Therapy is on a mission to serve as the trusted partner for therapists growing their practice, and patients accessing high-quality care. Powered by technology, we are a three-sided marketplace that empowers providers, augments insurance payors, and serves patients. Following the mass increase in depression and anxiety, the need for accessibility is more important than ever. To make our vision for mental healthcare a reality, we’re building a team of entrepreneurs and mission-driven go-getters. Since launching in February 2021, we’ve empowered more than ten thousand therapists and hundreds of thousands of clients across the country and insurance landscape. We’ve raised more than $178mm of funding from Sequoia Capital, Transformation Capital, TCV, SignalFire, and others.

About the Role

At Grow, we are building products that support people’s mental health and overall wellbeing. We believe meaningful research is critical to creating experiences that are not only usable, but genuinely helpful and human-centered.

We’re looking for a mid-level User Experience Researcher who is comfortable working across qualitative and quantitative methods and thrives in ambiguous, fast-moving environments. You’ll partner closely with Product, Design, and Business teams to uncover insights that shape strategy, inform design, and improve user outcomes.

This role is ideal for someone who is passionate about understanding people, curious about the intersection of technology and mental health, and motivated to advocate for users in impactful ways.

What You’ll Do

• Design and execute end-to-end research using a mix of methods (e.g., interviews, usability testing, surveys, focus groups, field studies)
• Develop and prioritize research plans in partnership with product and business teams
• Conduct studies that uncover both user behaviors and attitudes
• Synthesize findings into clear, actionable insights that inform product strategy and design decisions
• Communicate research outcomes through compelling storytelling, presentations, and deliverables
• Collaborate cross-functionally with Product, Design, Content, Engineering, and Marketing to guide decision-making
• Advocate for users by bringing their needs and perspectives into product development
• Navigate ambiguity and manage multiple projects in a fast-paced environment
• Promote inclusive, ethical research practices, especially within the mental health space

What We’re Looking For

• 5–8+ years of experience in UX research, product research, or a related field
• Mixed method researcher with strong experience in qualitative and quantitative research methods
• Proven track record of conducting research that has influenced product, design, or growth decisions
• Ability to move between evaluative (tactical) and generative (strategic) research
• Experience working cross-functionally in product-driven environments
• Strong communication and storytelling skills to influence diverse stakeholders

You’ll Be a Great Fit If You

• Thrive in collaborative, high-growth environments and enjoy helping teams make better decisions
• Are deeply curious and care about people and their experiences, and motivated to solve complex user problems, especially in mental health, healthcare, or multi-sided platforms
• Are comfortable navigating ambiguity and shaping direction in fast-changing environments
• Balance research rigor with pragmatism to drive efficient, impactful outcomes
• Bring a strong point of view while remaining adaptable and grounded in evidence
• Are motivated by impact and want your work to make a meaningful difference

Why Grow

• Work on products that directly impact mental health and wellbeing
• Collaborate with a team that values diverse perspectives and inclusive research
• Help shape how research drives decisions in a growing organization
• Contribute to building more human, ethical, and supportive technology
  
  

  Employment Type: Full Time
  Base Compensation: The base compensation range for this position is $182,000–$227,000 USD
  This is a hybrid role with the expectation to work onsite from our NYC, San Francisco, or Seattle hub location three days per week (Tuesday, Wednesday, and Thursday) and travel 2–3 times per year (e.g., company and department offsites).
  The base compensation for this role will vary depending on several factors, including relevant experience, qualifications, and the candidate’s working location.

We are looking for a Manager, Customer Success Engineering (AI & Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams.

As a Manager, CSE (AI & Cloud Support) at DigitalOcean, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. Reporting to the Senior Manager of Customer Success Engineering, you will own day-to-day support operations, team performance, and customer experience outcomes.

This role is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality.

The ideal candidate brings a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering “white-glove” experiences for strategic customers.

What You’ll Do:

Team Leadership & Development

• Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth
• Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.
• Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.
• Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.
• Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.
  
  

Strategic Customer Support

• Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.
• Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.
• Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.
• Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.

Technical & Cross-Functional Operations

• Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.
• Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product — including Jira escalation routing, Sev1 bridge management, and post-incident documentation.
•  Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content — treating documentation infrastructure as a core operational lever for team scalability.
• Contribute to the vision for AI and automation within support—building intelligent tooling and driving the team toward an automation-first model to improve efficiency, scalability, and customer experience.
• Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.

Key Metrics:

• Customer Satisfaction (CSAT) for strategic accounts
• Time to Response and Resolution (TTR) for strategic customers
• Tier 1 resolution rate vs. escalation rate
• Time-to-escalation and engineering handoff SLA adherence
• SLA adherence and escalation response times
• Support productivity and quality (QA scores)
• Post-incident documentation completion rate

What You’ll Add to DigitalOcean:

• Experience: 5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.
• Leadership: 2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.
• Technical Domain Expertise: Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps. Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.
• Coding/Integration: Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.
• Communication: Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.
• Problem-Solving: Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.

Preferred Qualifications:

• Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).
• Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• ITIL or equivalent service management certification

Compensation Range: 

• $125,000 - $153,000

*This is a remote role

JR: 2026-7692

#LI-Remote

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer 2 to join our AI Inference Engine Systems team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. You will work at the intersection of distributed systems and specialized AI hardware to ensure our customers can deploy and scale their models with industry-leading performance and reliability. This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. 

What You’ll Do:

• Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models.
• System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards.
• Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing.
• Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs.
• Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement.
• Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health.

What You’ll Bring to DigitalOcean:

• Distributed Systems Expertise: Strong experience with microservices, messaging systems, databases, and infrastructure as code.
• AI/ML Domain Knowledge: Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular.
• Inference Frameworks: Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.
• Hardware & Interconnects: Understanding of GPU-level optimization and experience with interconnect technologies like NVlink, XGMI, or RoCE.
• Architecture Proficiency: Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Software Engineering: Expert-level proficiency in GoLang or Python and familiarity with gRPC.
• Cloud Operations: Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean.
• Open Source Mindset: Experience integrating and building with open-source software.

Compensation Range: 

• $167,200.00 - $209,000

*This is a remote role

JR: 2026-7591

#LI-Remote

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer 2 to join our AI Inference Engine Systems team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. You will work at the intersection of distributed systems and specialized AI hardware to ensure our customers can deploy and scale their models with industry-leading performance and reliability. This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. 

What You’ll Do:

• Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models.
• System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards.
• Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing.
• Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs.
• Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement.
• Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health.

What You’ll Bring to DigitalOcean:

• Distributed Systems Expertise: Strong experience with microservices, messaging systems, databases, and infrastructure as code.
• AI/ML Domain Knowledge: Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular.
• Inference Frameworks: Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.
• Hardware & Interconnects: Understanding of GPU-level optimization and experience with interconnect technologies like NVlink, XGMI, or RoCE.
• Architecture Proficiency: Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Software Engineering: Expert-level proficiency in GoLang or Python and familiarity with gRPC.
• Cloud Operations: Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean.
• Open Source Mindset: Experience integrating and building with open-source software.

Compensation Range: 

• $167,200.00 - $209,000

*This is a remote role

JR: 2026-7591

#LI-Remote

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer 2 to join our AI Inference Engine Systems team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. You will work at the intersection of distributed systems and specialized AI hardware to ensure our customers can deploy and scale their models with industry-leading performance and reliability. This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. 

What You’ll Do:

• Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models.
• System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards.
• Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing.
• Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs.
• Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement.
• Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health.

What You’ll Bring to DigitalOcean:

• Distributed Systems Expertise: Strong experience with microservices, messaging systems, databases, and infrastructure as code.
• AI/ML Domain Knowledge: Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular.
• Inference Frameworks: Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.
• Hardware & Interconnects: Understanding of GPU-level optimization and experience with interconnect technologies like NVlink, XGMI, or RoCE.
• Architecture Proficiency: Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Software Engineering: Expert-level proficiency in GoLang or Python and familiarity with gRPC.
• Cloud Operations: Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean.
• Open Source Mindset: Experience integrating and building with open-source software.

Compensation Range: 

• $167,200.00 - $209,000

*This is a hybrid role

JR: 2026-7591

#LI-Hybrid

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer 2 to join our AI Inference Engine Systems team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. You will work at the intersection of distributed systems and specialized AI hardware to ensure our customers can deploy and scale their models with industry-leading performance and reliability. This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. 

What You’ll Do:

• Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models.
• System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards.
• Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing.
• Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs.
• Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement.
• Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health.

What You’ll Bring to DigitalOcean:

• Distributed Systems Expertise: Strong experience with microservices, messaging systems, databases, and infrastructure as code.
• AI/ML Domain Knowledge: Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular.
• Inference Frameworks: Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.
• Hardware & Interconnects: Understanding of GPU-level optimization and experience with interconnect technologies like NVlink, XGMI, or RoCE.
• Architecture Proficiency: Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Software Engineering: Expert-level proficiency in GoLang or Python and familiarity with gRPC.
• Cloud Operations: Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean.
• Open Source Mindset: Experience integrating and building with open-source software.

Compensation Range: 

• $167,200.00 - $209,000

*This is a remote role

JR: 2026-7591

#LI-Remote

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer II to join our AI Inference Engine Systems team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. You will work at the intersection of distributed systems and specialized AI hardware to ensure our customers can deploy and scale their models with industry-leading performance and reliability. This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. 

What You’ll Do:

• Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models.
• System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards.
• Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing.
• Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs.
• Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement.
• Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health.

What You’ll Bring to DigitalOcean:

• Distributed Systems Expertise: Strong experience with microservices, messaging systems, databases, and infrastructure as code.
• AI/ML Domain Knowledge: Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular.
• Inference Frameworks: Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.
• Hardware & Interconnects: Understanding of GPU-level optimization and experience with interconnect technologies like NVlink, XGMI, or RoCE.
• Architecture Proficiency: Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Software Engineering: Expert-level proficiency in GoLang or Python and familiarity with gRPC.
• Cloud Operations: Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean.
• Open Source Mindset: Experience integrating and building with open-source software.

Compensation Range: 

• $167,200.00 - $209,000

*This is a remote role

JR: 2026-7591

#LI-Remote

The Role:

We are seeking a highly skilled and experienced Senior Software Engineer to join our Kubernetes and Istio team to create high-quality solutions that simplify complex tasks and enhance developer productivity. You will have the opportunity to directly impact the direction and architecture of our cloud infrastructure, focusing on using Kubernetes and Istio on AWS. If you are a seasoned Software Engineer with a passion for building robust infrastructure solutions and a strong background in cloud technologies, we invite you to apply for this exciting opportunity.
 

What You’ll Do:

• Design, develop, and maintain software that enables developers to efficiently interact with our cloud infrastructure and services.

• Work closely with cross-functional teams to understand requirements and design solutions that are intuitive, efficient, scalable, and reliable.

• Provide technical leadership for the Cloud Platform team to design and implement strategies for optimizing cloud costs, resource utilization, and overall performance.

• Lead the development of software solutions to enable engineers to seamlessly use networking, compute, and storage services within AWS and Kubernetes environments.

• Identify opportunities for automation and process improvement to enhance developer productivity.

• Collaborate with cloud and software engineers to integrate solutions seamlessly into cloud environments.

• Conduct code reviews and provide constructive feedback to other team members.

• Stay up-to-date with the latest trends and technologies in cloud infrastructure and software engineering.
   

What You’ll Need:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.

• 3+ years of software development experience.

• Expertise in cloud platforms including AWS and cloud-native technologies.

• Strong programming fundamentals (ex: Java/Kotlin, Python, Go).

• Strong understanding of software design principles and best practices.

• Experience with container orchestration (e.g., Docker, Kubernetes - especially EKS), networking, and service meshes (especially Istio).

• Experience with infrastructure as code (IaC) tools and practices (e.g. Terraform).

• Familiarity with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI/CD).

• Excellent problem-solving skills and ability to think strategically about cloud infrastructure and platform design.

• Experience with generative AI coding agents such as Claude and Cursor. 
   

Preferred Qualifications:

• Experience with cloud storage solutions, compute resources management, and networking in AWS.

• Experience with monitoring and logging tools (e.g. Datadog).

• Experience with service discovery and load balancing solutions.

• Experience with security and compliance in cloud environments.

The Role

At SoFi, we’re on a mission to help our members get their money right. We are seeking a Principal Product Manager to lead the strategy and roadmap for our Fraud, Risk & ML Platform. This platform is the unified foundation for event-driven decisioning, risk-based interdictions, real-time feature stores, and self-serve ML capabilities across the enterprise.

You will shape SoFi’s risk and ML future, transforming complex backend processes into a seamless, self-serve platform that powers real-time decisioning for every SoFi product. Your goal is to accelerate organizational adoption of machine learning and expedite business growth by simplifying the integration of complex risk defenses that protect our members and the business.

What You’ll Do

• Strategic Roadmap: Own the multi-year vision for the Fraud, Risk & ML Platform, focusing on self-serve onboarding, reliability at scale, and superior developer experience.
• The "Model Factory": Direct the MLOps lifecycle to reduce model time-to-market from months to weeks. You will enable teams to build, deploy, and monitor ML models at enterprise scale.
• Platform Integration: Partner with internal product teams to identify friction in platform adoption and build features that eliminate integration pain points.
• Stakeholder Alignment: Drive onboarding for Fraud, AML, and Policy Engine use cases by aligning with Fraud, Risk, Data Science, and Infrastructure stakeholders on usage patterns, signals, features, and treatments, and guide execution teams to successfully deliver on those goals.
• Platform-as-a-Service: Drive Developer Experience (DX) as a core product feature; define clean APIs, versioning, SLAs, and documentation to reduce critical-path dependencies.
• Governance & Scalability: Establish a federated extension model for custom events, features, challenges, & actions to enable safe extensibility and cross-product reuse.
• Metrics & Impact: Define and track success metrics, including time-to-onboard, model deployment velocity, decision quality (e.g. precision/recall/F1), step‑up completion/abandon rates, and platform reliability.
• Flex into adjacent fraud initiatives, helping cover the gray space between domain detection/prevention improvements and platform onboarding/utilization.
• Evangelism: Educate partner teams on platform capabilities to ensure SoFi is fully leveraging centralized infrastructure rather than building bespoke silos.

What You’ll Need

• 7+ years of Product Management experience: with a focus on platform, infrastructure, or developer-facing products
• Technical fluency: Deep familiarity with APIs, event-driven systems (sync/async), high-throughput data pipelines, ML lifecycle (training, features, deployment, monitoring), risk decisioning engines/workflows
• ML Infrastructure: Proven experience operationalizing models in production using tools like Snowflake, Flink/streaming, Kafka, or AWS/SageMaker
• Platform mindset:  A strong bias for normalization and generic, self-serve capabilities over bespoke builds.
• Exceptional Communication & Evangelism: ability to translate complex risk policy, business goals, and technical constraints into precise platform requirements, while rallying teams around a clear, forward-looking platform roadmap and strategy.
• Adaptive leadership: team‑first, able to navigate the gray space between domain‑specific fraud detection and horizontal platform utilization
• Direct experience with fraud and risk detection and prevention challenges and techniques. 

Nice to Have

• Experience with risk decisioning, rules engines, risk mitigations and step-up challenges. 
• Experience in FinTech or highly regulated financial environments.
• Background in building or scaling Generative AI for task‑automating agents (agentic workflows)
• Direct experience partnering with Data Science and MLEs to productionalize real-time scoring.

The role:

As a Senior Product Manager for Underwriting, you will be at the heart of SoFi’s lending engine. You will own the product lifecycle for the platforms and services that determine how we evaluate risk and qualify members for our lending products.

Your mission is to build scalable, high-performance underwriting infrastructure that balances member experience with rigorous risk controls. You won't just be managing a backlog; you will be driving tech capabilities that span across multiple organizations—partnering with Risk, Engineering, Data Science, and Legal to ensure our decisioning engines are fast, accurate, and compliant.  You excel at navigating complex technical dependencies and delivering measurable improvements to the underwriting squad.What you'll do: Own the Underwriting Roadmap: Define and drive the roadmap for our core underwriting and decisioning platforms, ensuring they support SoFi’s multi-product growth.

• Navigate Complexity: Drive tech capabilities and stakeholder buy-in across multiple organizations (Risk, Engineering, Legal, Compliance); effectively manage 3rd party partner integrations.
• Execution Excellence: Lead technical sprints, manage a complex backlog, and prioritize initiatives that improve underwriting throughput and reduce cycle times.
• Bridge the Gap: Translate nuanced risk and policy requirements into clear technical specifications for engineering teams, ensuring "underwriting thinking" is integrated from inception.
• Data-Driven Decision Making: Synthesize inputs from multiple sources (UXR, data analysis, finance) to build strategic rationales. Leverage SQL to track performance and inform prioritization.
• Process Improvement: Drive quality and velocity improvements by removing hurdles for the team and contributing to PM best practices within the Underwriting org.
• Stakeholder Management: Serve as the primary point of contact for underwriting technology, managing expectations and leading change management across the business.

What you’ll need:

• Experience: 5+ years of product management experience, ideally within fintech, lending, or platform-side roles.
• Technical Depth: Strong understanding of system architecture; ability to opine on technical choices and understand the trade-offs of different technical frameworks.
• Communication: Excellent communication skills—able to engage seamlessly with technical, analytical, and business audiences.
• Analytical Skills: Fluency with SQL and data analysis; experience using data to address customer pain points and iterate into solutions.
• Influence: Proven ability to influence beyond your immediate team and foster cross-functional alignment in a matrixed environment.
• Project Management: Strong organizational skills with a track record of running technical sprints and complex product launches.

Nice to have: 

• Direct experience building or scaling underwriting/decisioning platforms.
• Knowledge of credit risk modeling and credit bureau data integrations.
• Experience working with lending platforms
• Experience working with LLMs or generative AI

About Trase

Co-founded in 2023 by Joe Laws and Grant Verstandig, Trase Systems is AI, Uncomplicated. Trase empowers enterprise leaders to harness the full potential of AI without the associated complexity and risks. We are an end-to-end solution for deploying, managing, and optimizing AI in the enterprise. Our platform specializes in bridging the “last mile” of AI adoption, unlocking AI's full potential while driving efficiency and significant cost savings. Trase is at the forefront of AI Agent innovation, topping the Hugging Face GAIA Leaderboard for Generalized AI Assistants, ahead of industry giants such as Google, Meta, Microsoft, and OpenAI. We are leveraging our cutting-edge technologies to develop mission-critical agentic applications in complex industries such as Healthcare, Oil & Gas, and National Security. 

About the Role

As a Principal Applied ML Researcher, you will define and drive the ML and LLM strategy for Trase OS, the agentic execution platform powering deployments in regulated environments.

You are responsible for how models behave inside real production systems - including agent workflows, tool use, and long-lived execution -not just offline model performance.

This is a hands-on technical leadership role operating at the intersection of research, systems, and product. You will drive technical breakthroughs in agentic infrastructure and applied AI systems, own the end-to-end research-to-production lifecycle, and set the standard for how ML systems are designed, evaluated, and deployed across Trase.

Why This Role Exists

Trase OS coordinates long-lived agents, multi-step workflows, tool-augmented LLMs, and execution in regulated environments.

As the system scales, the core challenge shifts from model capability to system correctness and reliability, where models may succeed offline but fail in real workflows, agent behavior can become unpredictable or unsafe, evaluation can drift from real outcomes, and ML decisions can introduce system-level instability.

This role defines how ML systems are integrated into execution systems, evaluated end-to-end, and operated reliably in production.

Responsibilities

Technical Leadership & Innovation

• Drive technical breakthroughs in agentic systems, applied ML infrastructure, and LLM-based applications.
• Define and evolve the ML/LLM strategy and technology roadmap in alignment with product development.
• Act as a principal technical authority, making high-impact architectural and modeling decisions across teams.

Research → Prototype → Production

• Develop prototypes for key technologies to validate new approaches and de-risk system design.
• Own the full lifecycle from research and experimentation through production deployment, monitoring, and iteration.
• Translate advances in ML into scalable, production-grade systems with measurable impact.

Agentic Systems & Applied ML

• Design how LLMs operate within agent workflows, tool use, and multi-step reasoning and long-lived execution.
• Implement and refine prompting strategies, multi-agent orchestration, memory management, and human-in-the-loop controls for safety and reliability.
• Establish patterns for planning, decision-making, and tool orchestration within complex systems.

Evaluation, Quality & Reliability

• Own end-to-end quality evaluation of ML-powered systems, including defining metrics, benchmarks, and testing frameworks.
• Establish evaluation systems that connect model performance to task success and system-level outcomes.
• Ensure systems behave predictably, safely, and reliably in production through monitoring, regression testing, and robust failure handling.

ML Systems & Platform Integration

• Contribute to the design of ML systems supporting the full lifecycle, including training, fine-tuning, evaluation, deployment, and monitoring.
• Drive architecture decisions across model serving, routing, orchestration, and latency and cost optimization.
• Work across infrastructure layers, including cloud and containerized systems, to ensure scalable and efficient deployment.

Enterprise & Regulated Deployments

• Build and deploy enterprise-grade AI systems used by global customers in production environments.
• Design systems that operate reliably in regulated and constrained settings, including on-premise, air-gapped, and secure cloud environments.
• Ensure systems are auditable, explainable, and compliant with regulatory and organizational requirements.

Communication & Influence

• Write technical reports and design documents summarizing R&D progress, system behavior, and key decisions.
• Communicate complex ML concepts and tradeoffs clearly to both technical and non-technical stakeholders.
• Drive alignment across research, engineering, and product through strong technical leadership.

Mentorship & Organizational Impact

• Mentor junior and senior engineers and researchers, raising the bar for ML rigor and system-level thinking.
• Establish and propagate best practices for ML system design, evaluation, and reliability across the organization.
• Influence technical direction beyond immediate teams through high-impact, cross-functional work.

Requirements

• 12–15+ years of experience in machine learning, including building and deploying applied ML systems in production environments.
• Strong programming skills in Python, with experience in Java, C++, or related languages in systems contexts.
• Deep expertise in at least one major ML domain, such as LLMs and generative AI, NLP or multimodal systems, deep learning, or graph learning.
• Hands-on experience with prompt engineering, multi-agent orchestration, tool integration via APIs, memory management, and human-in-the-loop system design.
• Proven experience building and shipping enterprise-grade AI systems, including GenAI, LLM, or agent-based applications at scale.
• Experience designing and implementing evaluation frameworks, including metrics, benchmarks, and testing systems.
• Strong understanding of ML system behavior in production, including reliability, latency, cost tradeoffs, and failure modes.
• Experience deploying ML systems in regulated or constrained environments and familiarity with modern ML infrastructure such as cloud platforms and containerized systems.
• Demonstrated ability to lead technical direction across teams and drive systems from concept to production impact.

Nice to Have

• Experience working with agent-based systems, retrieval-augmented generation, RLHF, or synthetic data approaches.
• Experience building and operating AI/ML platforms that support the full model lifecycle.
• Experience optimizing ML inference in real-time, distributed, or resource-constrained environments.
• Familiarity with data privacy, compliance, and responsible AI frameworks relevant to regulated industries.
• Prior experience operating at the Staff or Principal level in a scaling organization.

Salary Range: $230,000-300,000. This represents the typical salary range for this position based on experience, skills, and other factors.

#LI-RCP 

About the Role

As a Principal Applied ML Researcher, you will define and drive the ML and LLM strategy for Trase OS, the agentic execution platform powering deployments in regulated environments.

You are responsible for how models behave inside real production systems - including agent workflows, tool use, and long-lived execution -not just offline model performance.

This is a hands-on technical leadership role operating at the intersection of research, systems, and product. You will drive technical breakthroughs in agentic infrastructure and applied AI systems, own the end-to-end research-to-production lifecycle, and set the standard for how ML systems are designed, evaluated, and deployed across Trase.

Why This Role Exists

Trase OS coordinates long-lived agents, multi-step workflows, tool-augmented LLMs, and execution in regulated environments.

As the system scales, the core challenge shifts from model capability to system correctness and reliability, where models may succeed offline but fail in real workflows, agent behavior can become unpredictable or unsafe, evaluation can drift from real outcomes, and ML decisions can introduce system-level instability.

This role defines how ML systems are integrated into execution systems, evaluated end-to-end, and operated reliably in production.

Responsibilities

Technical Leadership & Innovation

• Drive technical breakthroughs in agentic systems, applied ML infrastructure, and LLM-based applications.
• Define and evolve the ML/LLM strategy and technology roadmap in alignment with product development.
• Act as a principal technical authority, making high-impact architectural and modeling decisions across teams.

Research → Prototype → Production

• Develop prototypes for key technologies to validate new approaches and de-risk system design.
• Own the full lifecycle from research and experimentation through production deployment, monitoring, and iteration.
• Translate advances in ML into scalable, production-grade systems with measurable impact.

Agentic Systems & Applied ML

• Design how LLMs operate within agent workflows, tool use, and multi-step reasoning and long-lived execution.
• Implement and refine prompting strategies, multi-agent orchestration, memory management, and human-in-the-loop controls for safety and reliability.
• Establish patterns for planning, decision-making, and tool orchestration within complex systems.

Evaluation, Quality & Reliability

• Own end-to-end quality evaluation of ML-powered systems, including defining metrics, benchmarks, and testing frameworks.
• Establish evaluation systems that connect model performance to task success and system-level outcomes.
• Ensure systems behave predictably, safely, and reliably in production through monitoring, regression testing, and robust failure handling.

ML Systems & Platform Integration

• Contribute to the design of ML systems supporting the full lifecycle, including training, fine-tuning, evaluation, deployment, and monitoring.
• Drive architecture decisions across model serving, routing, orchestration, and latency and cost optimization.
• Work across infrastructure layers, including cloud and containerized systems, to ensure scalable and efficient deployment.

Enterprise & Regulated Deployments

• Build and deploy enterprise-grade AI systems used by global customers in production environments.
• Design systems that operate reliably in regulated and constrained settings, including on-premise, air-gapped, and secure cloud environments.
• Ensure systems are auditable, explainable, and compliant with regulatory and organizational requirements.

Communication & Influence

• Write technical reports and design documents summarizing R&D progress, system behavior, and key decisions.
• Communicate complex ML concepts and tradeoffs clearly to both technical and non-technical stakeholders.
• Drive alignment across research, engineering, and product through strong technical leadership.

Mentorship & Organizational Impact

• Mentor junior and senior engineers and researchers, raising the bar for ML rigor and system-level thinking.
• Establish and propagate best practices for ML system design, evaluation, and reliability across the organization.
• Influence technical direction beyond immediate teams through high-impact, cross-functional work.

Requirements

• 12–15+ years of experience in machine learning, including building and deploying applied ML systems in production environments.
• Strong programming skills in Python, with experience in Java, C++, or related languages in systems contexts.
• Deep expertise in at least one major ML domain, such as LLMs and generative AI, NLP or multimodal systems, deep learning, or graph learning.
• Hands-on experience with prompt engineering, multi-agent orchestration, tool integration via APIs, memory management, and human-in-the-loop system design.
• Proven experience building and shipping enterprise-grade AI systems, including GenAI, LLM, or agent-based applications at scale.
• Experience designing and implementing evaluation frameworks, including metrics, benchmarks, and testing systems.
• Strong understanding of ML system behavior in production, including reliability, latency, cost tradeoffs, and failure modes.
• Experience deploying ML systems in regulated or constrained environments and familiarity with modern ML infrastructure such as cloud platforms and containerized systems.
• Demonstrated ability to lead technical direction across teams and drive systems from concept to production impact.

Nice to Have

• Experience working with agent-based systems, retrieval-augmented generation, RLHF, or synthetic data approaches.
• Experience building and operating AI/ML platforms that support the full model lifecycle.
• Experience optimizing ML inference in real-time, distributed, or resource-constrained environments.
• Familiarity with data privacy, compliance, and responsible AI frameworks relevant to regulated industries.
• Prior experience operating at the Staff or Principal level in a scaling organization.

Salary Range: $230,000-300,000. This represents the typical salary range for this position based on experience, skills, and other factors.

#LI-RCP 

Summary:

As the Vice President, Ads Quality Engineering, you will spearhead our AIML engineering division, dedicated to leveraging data machine learning innovations, and the vanguard of AI to enhance Pinterest's ads delivery funnel. Possessing robust analytical skills, a deep understanding of machine learning and generative AI, online auction dynamics, and previous experience leading substantial engineering teams, you will push the boundaries of current AIML applications, multi-party marketplace behavior, and auction theory. Your efforts will be crucial in maximizing Pinterest's monetization opportunities.

This pivotal role grants you the autonomy to collaborate extensively across the organization, aligning interests and strategies among pinners, content creators, and advertisers in our distinct marketplace. Your leadership will be instrumental in shaping advanced ML solutions that not only define industry standards but also drive substantial business impact.

What you’ll do:

• Oversee a globally distributed  team of 200+ AI/ML engineers tasked with harnessing data-driven insights and developing solutions to bolster Pinterest’s monetization efforts.
• Provide both technical and organizational leadership to scale the team in response to evolving business demands.
• Manage and develop senior leadership within the team, including managers of managers and principal AI/ML experts, ensuring growth and continuous improvement at all levels.
• Partner closely with engineering and product leadership to shape and drive the execution of Pinterest's monetization strategy.
• Foster strong cross-functional (XFN) collaborations across multiple departments, including Sales, Business Operations, Data Engineering, and Core Services, to ensure cohesive efforts and optimal outcomes in monetization strategies.

What we’re looking for:

• An MSc or PhD degree in Economics, Statistics, Computer Science, or a related field.
• A minimum of 15 years of relevant industry experience, demonstrating a depth of technical proficiency and leadership.
• At least 10 years of experience in managerial roles, with a proven track record of effective team leadership and development.
• Exceptional cross-functional (XFN) collaboration skills and a strong capability in communication, crucial for liaising seamlessly across departments.
• A natural bridge-builder, skilled in fostering alignment and driving strategic initiatives within the engineering and product organization at Pinterest.
• Hands-on experience in designing and deploying large-scale machine learning systems, with a preference for those possessing specific expertise in the Advertising domain.
• Strong analytical abilities, underpinned by a solid foundation in mathematical and statistical models, enabling sophisticated problem-solving and innovation.

Relocation Statement:

•  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration once or twice a week and therefore needs to be in a commutable distance from one of the following offices: Palo Alto, San Francisco, Seattle, or Los Angeles.

#LI-HYBRID

#LI-RR4

SUMMARY

Pinterest helps Pinners discover and do what they love, and enable advertisers to effectively engage with the ideal audience to meet their marketing objectives. Pinterest has grown into one of the world's largest consumer products and advertising platforms, boasting over 600 million monthly active users and generating more than $4 billion in annualized advertising revenue. Our ongoing business success is reliant on our capacity to accelerate product innovation, which in turn allows us to deliver increased value to both our Pinners and Advertisers. For advertisers, Pinterest is a uniquely powerful platform where people actively seek out ideas and products, creating unparalleled purchase intent. 

Pinterest's Ads Quality team sits at the heart of our monetization engine — Pinners with the brands and products most relevant to their moments of inspiration. Reporting to Pinterest’s VP & GM of Monetization, the Senior Director of Product Management, Ads Quality, will own the end-to-end product vision and strategy for one of Pinterest's most significant and technically sophisticated domains.

The Senior Director of Product Management, Ads Quality will lead a team of 10–15 Product Managers, partnering at the highest levels across Engineering, Data Science, Machine Learning, Sales, and Go-to-Market to shape the future of advertising at Pinterest. They will be the strategic architect behind how we optimize for Pinner experience, advertiser outcomes, and Pinterest's long-term business growth — simultaneously and at scale.

The ideal candidate is an experienced product executive who brings deep expertise in digital advertising and ML-powered products, a strong executive presence, and a proven track record of building and inspiring high-performing PM organizations in complex, fast-moving environments.

What You’ll Do: 

• Set and drive organizational vision: Define and champion a multi-year product strategy for Pinterest's Ads Quality portfolio, ensuring alignment across business objectives, technical capabilities, and evolving market dynamics in digital advertising.
• Lead a high-impact PM organization: Build, mentor, and inspire a team of 10–15 senior Product Managers, fostering a culture of product excellence, strategic rigor, and cross-functional collaboration.
• Shape the ML and AI technology roadmap: Partner with senior Engineering and ML leadership to guide the evolution of Pinterest's machine learning and generative AI technology stack, translating cutting-edge capabilities into differentiated advertising experiences.
• Drive advertiser and Pinner value creation: Own the strategic balance between delivering measurable ROI for advertisers and preserving the authentic, high-quality inspiration experience that makes Pinterest unique.
• Influence at the executive level: Serve as a key voice in monetization strategy discussions with C-suite and VP-level stakeholders, representing Ads Quality priorities and translating complex technical tradeoffs into clear business narratives.
• Accelerate go-to-market impact: Partner with Product Marketing and Sales leadership to bring new advertising products to market, from ideation through launch and scaled growth.
• Cross functional collaboration: Partner with the Engineering, Sales, Finance, and Legal teams to develop and implement measurement solutions while also helping with Advertiser and client facing technical communication. 

What We’re Looking For: 

• 15+ years of product leadership experience, with a significant tenure in advertising technology, or data-driven marketing platforms
• A proven track record of building and scaling ads products that have materially driven revenue and business growth
• Executive presence and influence — experience presenting product vision to senior stakeholders and partnering closely with engineering teams to execute on roadmap
• Experience leading large, high-performing PM organizations and developing the next generation of product leaders
• A strategic mindset backed by strong analytical and data fluency, including comfort with ML/AI-driven product development
• History of navigating complexity and driving alignment across large, matrixed organizations
• Bachelor’s or Master’s degree in Computer Science or related field 

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement: 

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration at least 1-2 times per week and therefore needs to be in a commutable distance from the Pinterest Palo Alto, San Francisco, Seattle, or Los Angeles office. The role will also require regular travel within the country to meet clients and teams. 

#LI-HYBRID 

#LI-RR4

As a machine learning intern in our Advance Technology Group at Pinterest, you will be exposed to a full spectrum of ML product development. The team focuses on developing cutting-edge technologies for Pinterest’s visual understanding modules and recommender systems.  You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also having opportunities to deploy features to hundreds of millions of users or conduct research applicable for paper submissions. We offer a 12-week fall internship program remotely or in our San Francisco, Palo Alto, Seattle, or New York offices.

Note to applicants:

By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process.

Internships are 12 weeks paid from September 21 - December 11, 2026. Depending on the team, our fall internships will be located either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices.

What you’ll do:

• Develop and launch new user features using unique internal datasets and ML techniques, especially in recommendation systems, computer vision, representation learning, generative AI, and responsible AI.
• Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
• Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
• Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
• Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
• Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
• Write clean, efficient, and sustainable code
• Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers

What we’re looking for:

• This role will be on our Visual Search or Applied Science teams. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization, Generative AI, and LLMs. 
• Ability to legally work full time (40 hours/week) from September-December 2026
• Working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
• Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow)
• Proficiency with AI-native engineering, including the design of agent-friendly codebases.
• High degree of autonomy in learning new agent-first development tools.
• Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.
• Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.
• Experience in research and in solving analytical problems
• Strong communicator and team player. Being able to find solutions for open-ended problems.

Preferred Qualifications:

• • Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields
  • Strong passion for research and for answering hard questions with research
  • Passion for applied ML and the Pinterest product

Why Intern at Pinterest?

• Meaningful Work: Contribute to projects that impact millions of users worldwide.
• Mentorship: Learn from and be guided by experienced engineers and researchers in the field.
• Growth and Development: Participate in professional development workshops and networking events to build your skills and connections.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we’re not always working in an office, but we continue to gather for key moments of collaboration and connection
• This role may require you to be located near an office for in-person collaboration, and therefore may need to be located a commutable distance from one of our Pinterest offices.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

The salary for this position is $12,100 monthly.

#LI-HYBRID
#LI-EB1

As a machine learning intern in our Advance Technology Group at Pinterest, you will be exposed to a full spectrum of ML product development. The team focuses on developing cutting-edge technologies for Pinterest’s visual understanding modules and recommender systems.  You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also having opportunities to deploy features to hundreds of millions of users or conduct research applicable for paper submissions. We offer a 12-week fall internship program remotely or in our San Francisco, Palo Alto, Seattle, or New York offices.

Note to applicants:

By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process.

Internships are 12 weeks paid from September 21 - December 11, 2026. Depending on the team, our fall internships will be located either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices.

What you’ll do:

• Develop and launch new user features using unique internal datasets and ML techniques, especially in computer vision, generative AI, and responsible AI.
• Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
• Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
• Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
• Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
• Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
• Write clean, efficient, and sustainable code
• Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers

What we’re looking for:

• This role will be on our Visual Search team. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Generative AI, and LLMs. 
• Ability to legally work full time (40 hours/week) from September-December 2026
• Working towards a Master's degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
• Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow)
• Proficiency with AI-native engineering, including the design of agent-friendly codebases.
• High degree of autonomy in learning new agent-first development tools.
• Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.
• Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.
• Experience in research and in solving analytical problems
• Strong communicator and team player. Being able to find solutions for open-ended problems.

Preferred Qualifications:

• • Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields
  • Strong passion for research and for answering hard questions with research
  • Passion for applied ML and the Pinterest product

Why Intern at Pinterest?

• Meaningful Work: Contribute to projects that impact millions of users worldwide.
• Mentorship: Learn from and be guided by experienced engineers and researchers in the field.
• Growth and Development: Participate in professional development workshops and networking events to build your skills and connections.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we’re not always working in an office, but we continue to gather for key moments of collaboration and connection
• This role may require you to be located near an office for in-person collaboration, and therefore may need to be located a commutable distance from one of our Pinterest offices.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

The salary for this position is $11,00 monthly.

#LI-HYBRID
#LI-EB1

We're building a new capability at Pinterest: embedding AI-native engineering directly inside our business functions. The AI Solutions Engineer will partner with teams across Marketing, Finance, Sales, HR, Legal, and other functions to surface high-value automation opportunities, then design and ship the AI-powered tools that bring those opportunities to life.

This is a hands-on, mid-level software engineering role for someone who is equally comfortable reading a business process flowchart and writing production-grade Python. You'll work end-to-end — from discovery and scoping through prototyping, launch, and iteration — using the latest agentic frameworks, tool-calling patterns, and responsible AI practices.

What you'll do:

• Discover and scope AI opportunities: Partner with internal teams across corporate functions to understand their workflows, pain points, and goals, and identify high‑value AI/automation opportunities. Map and improve business processes: document current workflows, identify bottlenecks, and propose AI‑enabled changes that deliver clear business outcomes (e.g., time or cost savings, improved quality or compliance).
• Design end-to-end AI solutions: Design and implement AI‑enabled tools and workflows that integrate with existing systems and data sources, and that are intuitive for non‑technical users.
• Build and ship production-quality software: Write clean, maintainable code and tests. Use standard CI/CD and environment practices. Implement logging, monitoring, and basic guardrails so we can understand and improve performance, quality, cost, and reliability over time.
• Pilot, rollout, and drive adoption: Pilot, roll out, and drive adoption of solutions by working closely with end‑users, gathering feedback, and iterating based on real‑world usage.
• Champion for responsible AI: Ensure solutions follow privacy, security, and compliance expectations, especially when working with sensitive or regulated data.
• Build for reuse: Create and share reusable patterns, components, and documentation to make future AI/automation work faster and more consistent across teams.
• Accelerate Workflows with Generative AI and Automation: Leverage AI to accelerate execution (e.g., draft, prototype, outline), explore alternative solutions using AI (iterate, compare approaches), synthesize information with AI (summarize, distill key themes), automate repeatable work (documentation, reporting, QA checks)

What we're looking for:

We're looking for mid-level engineers who have already shipped something real with AI — and who can work as a peer with non-technical business partners, not just as an order-taker. Specifically, you bring:

• Software engineering foundation. A CS, Engineering, Data Science, or related degree (or equivalent experience), with demonstrated ability to build and operate production systems — backend services, internal tools, integrations, or data applications.
• Hands-on AI and automation delivery. You've shipped AI-powered or automation-driven solutions in a real environment. Examples include: a multi-step workflow automation, an internal tool using document understanding or intelligent routing, or an integration of an AI service (e.g., OpenAI, Anthropic, Vertex AI, Bedrock) into an existing system.
• Agentic AI literacy. You understand how modern agentic systems are constructed — the difference between local and remote agents, how MCP (Model Context Protocol) works, what Agent Skills and Hooks are for, and how A2A (Agent-to-Agent) coordination is structured. You can reason about when to use these patterns and when simpler approaches suffice.
• System design and architecture thinking. You can sketch a data flow, reason about integration points, evaluate trade-offs between approaches, and design for failure — including fallbacks, retry logic, timeouts, and human escalation paths.
• Data and security judgment. You understand data access controls, the risks of giving AI broad access to sensitive information, PII minimization, audit logging, and what responsible data handling looks like in an enterprise environment. You know to filter data before it reaches the model, not after.
• Business function acumen. You can engage credibly with stakeholders in Marketing, Finance, Sales, HR, Legal, or Operations — understanding their workflows, KPIs, and constraints well enough to scope solutions that fit their real needs.
• Clear, collaborative communication. You can explain architecture trade-offs to a Finance Manager and debug a prompt failure with an engineer in the same afternoon. You build trust by being direct about limitations, not by over-promising.
• Preferred Qualifications
  • Experience working embedded with or alongside corporate / G&A functions (Finance, Legal, HR, Marketing, Sales Operations, or similar).
  • Practical experience with agentic frameworks such as LangGraph, Claude Agent SDK, or comparable tooling
  • Familiarity with MCP server design — including building, deploying, and securing MCP-compliant tool servers.
  • Experience designing and evaluating AI outputs at scale: eval sets, sampling pipelines, human-in-the-loop review queues, or A/B testing of AI-powered features.
  • Exposure to responsible AI frameworks: data minimization, differential privacy concepts, model output auditing, or working in PII-sensitive / regulated domains.
  • Experience with RAG (Retrieval-Augmented Generation) pipelines, vector databases, or enterprise search integrations.
  • Familiarity with CI/CD for AI: prompt versioning, model version pinning, regression testing for LLM-powered features.
  • Bachelor’s/Master’s degree in a relevant field such as Computer Science or equivalent experience.
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  
  

In-Office Requirement Statement:

•  This role will need to be in the office for in-person collaboration 1-2 times every 6-months and therefore can be situated anywhere in the country.
  
  

#LI-REMOTE

#LI-KBF

What we’re looking for

SurveyMonkey is reimagining how people gather insights by bringing AI directly into the survey workflow. This role will play a critical part in building the platform and product capabilities that enable these AI-driven experiences. The work you lead will directly influence how millions of users interact with the product and unlock entirely new ways for organizations to collect and act on feedback. In this role, you will report to the Senior Director of Product Management and will partner closely with engineering, AI/ML, design, and data science teams to deliver against this vision.

What you’ll be working on

• Partner with product leadership to define AI and agentic capabilities that power the product
• Own the roadmap for the key components of the AI platform, including orchestration layers, tool/action frameworks, context management, and evaluation pipelines
• Partner closely with AI/ML, platform engineering, design, and data science teams to ship scalable capabilities that integrate LLMs, internal APIs, and product workflows
• Establish evaluation frameworks and success metrics for AI and agentic capabilities
• Define guardrails, reliability standards, and safe execution mechanisms to ensure AI operates predictably and securely within the SurveyMonkey ecosystem
• Drive cross-functional alignment across engineering, design, data, GTM, and leadership to launch greenfield AI capabilities at scale.

We’d love to hear from people with

• 5+ years of product management experience building and launching SaaS products
• 2+ years of experience launching AI-powered products involving generative AI and conversational interfaces.
• 3+ years defining ML platform capabilities, including model development, integration, evaluation pipelines, data feedback loops, and platform APIs
• Strong understanding of AI frameworks and architectures with deep knowledge of evals, and context management (technical fluence around these components is expected)
• Experience writing lightweight code to prototype AI capabilities
• Demonstrated experience building 0→1 products or greenfield capabilities, navigating ambiguity and driving initiatives from concept to launch.
• Experience defining clear product metrics and success frameworks, including adoption, engagement, task success, model quality, and business impact.
• Ability to work deeply with engineering and ML teams, translating technical constraints into product decisions and vice versa.

Nice to Have

• Product management experience working across both consumer and enterprise SaaS products 
• Past experience with product development leveraging Open AI for enterprise and AWS technologies like AWS Bedrock and SageMaker
• Curiosity and enthusiasm for staying on top of rapidly evolving AI technologies, tools, and frameworks

The base pay provided for this position ranges from $147,900/ year - $191,400/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses and commissions may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits.

SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution. While this role is remote, it may require in-person participation. You will be encouraged to attend company events throughout the year. These events will take place at a designated SurveyMonkey office or location.

#LI-remote

What we’re looking for

SurveyMonkey is reimagining how people gather insights by bringing AI directly into the survey workflow. This role will play a critical part in building the platform and product capabilities that enable these AI-driven experiences. The work you lead will directly influence how millions of users interact with the product and unlock entirely new ways for organizations to collect and act on feedback. In this role, you will report to the Senior Director of Product Management and will partner closely with engineering, AI/ML, design, and data science teams to deliver against this vision.

What you’ll be working on

• Partner with product leadership to define AI and agentic capabilities that power the product
• Own the roadmap for the key components of the AI platform, including orchestration layers, tool/action frameworks, context management, and evaluation pipelines
• Partner closely with AI/ML, platform engineering, design, and data science teams to ship scalable capabilities that integrate LLMs, internal APIs, and product workflows
• Establish evaluation frameworks and success metrics for AI and agentic capabilities
• Define guardrails, reliability standards, and safe execution mechanisms to ensure AI operates predictably and securely within the SurveyMonkey ecosystem
• Drive cross-functional alignment across engineering, design, data, GTM, and leadership to launch greenfield AI capabilities at scale.

We’d love to hear from people with

• 5+ years of product management experience building and launching SaaS products
• 2+ years of experience launching AI-powered products involving generative AI and conversational interfaces.
• 3+ years defining ML platform capabilities, including model development, integration, evaluation pipelines, data feedback loops, and platform APIs
• Strong understanding of AI frameworks and architectures with deep knowledge of evals, and context management (technical fluence around these components is expected)
• Experience writing lightweight code to prototype AI capabilities
• Demonstrated experience building 0→1 products or greenfield capabilities, navigating ambiguity and driving initiatives from concept to launch.
• Experience defining clear product metrics and success frameworks, including adoption, engagement, task success, model quality, and business impact.
• Ability to work deeply with engineering and ML teams, translating technical constraints into product decisions and vice versa.

Nice to Have

• Product management experience working across both consumer and enterprise SaaS products 
• Past experience with product development leveraging Open AI for enterprise and AWS technologies like AWS Bedrock and SageMaker
• Curiosity and enthusiasm for staying on top of rapidly evolving AI technologies, tools, and frameworks

The base pay provided for this position ranges from CAD $133,450.00/year - $157,000.00/year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution in problem-solving and decision-making. As such, you will be required to work from our Ottawa office up to 1 day per week.

#LI-Hybrid

The Role 

We’re hiring a Senior Forward Deployed Engineer to lead implementations of our AI platform directly with customers. This role is ideal for an experienced technically fluent builder who thrives at the intersection of engineering and problem solving; someone who wants to be hands-on with code while shaping how some of the world’s most recognizable brands modernize their content operations.

As a Senior FDE, you’ll own full-stack development for enterprise deployments, working side-by-side with customers to map complex workflows into scalable generative systems. You’ll move between discovery, prototyping, implementation, and post-launch optimization - translating real-world pain points into elegant technical solutions.

What You'll Own

• Lead technical discovery and implementation for new enterprise customers, translating nuanced business processes into robust AI-native solutions.
• Build, deploy and optimize features that integrate customer systems with Gradial’s LLM driven platform.
• Develop reusable tools, adapters and configuration layers to support scalable enterprise onboarding.
• Collaborate with customer stakeholders (mainly within marketing, operations and engineering) to define requirements, surface edge cases and iterate in real time.
• Work closely with Gradial’s product and engineer teams to incorporate learnings from the field into our core roadmap.
• Contribute to internal technical documentation and implementation playbooks that accelerate future deployments.
• Own performance, reliability and maintainability for the solutions you ship, from backend architecture to customer UX.

What We're Looking For

• 5+ years of software engineering or technical implementation experience, ideally in customer-facing contexts.
• Experienced in programming languages such as TypeScript or similar, with a strong understanding of APIs and systems integration.
• Ability to rapidly understand unfamiliar technical ecosystems (CMS, DAM, workflow tools) and build integration paths.
• Excellent communication skills. Confident translating for both technical and non-technical stakeholders.
• High ownership mindset with comfort operating independently, navigating ambiguity.
• Demonstrated experience working with enterprise customers; particularly in content, marketing or digital operations.
• Experience with LLMs, generative AI pipelines and agent-style automation frameworks.
• Prior consulting, technical solution engineering or internal tools engineering experience.
• Willingness to travel occasionally (<10%) for customer discovery, deployment and relationship building.

Compensation 

The salary range for this position is $130,000 – $210,000 annually. Final compensation will be determined based on factors such as experience, skills, and qualifications. In addition to base salary, this role may be eligible for performance-based bonuses and equity awards. Gradial offers a comprehensive benefits package, including medical, dental & vision insurance, 401K retirement plan, paid time off, paid sick leave and other employee wellness programs. 

The Role

We’re hiring a Forward Deployed Engineer to lead implementations of our AI platform directly with customers. This role is ideal for a technically fluent builder who thrives at the intersection of engineering and problem solving; someone who wants to be hands-on with code while shaping how some of the world’s most recognizable brands modernize their content operations.

As an FDE, you’ll own full-stack development for enterprise deployments, working side-by-side with customers to map complex workflows into scalable generative systems. You’ll move between discovery, prototyping, implementation, and post-launch optimization - translating real-world pain points into elegant technical solutions.

What You'll Own

• Lead technical discovery and implementation for new enterprise customers, translating nuanced business processes into robust AI-native solutions.
• Build, deploy and optimize features that integrate customer systems with Gradial’s LLM driven platform.
• Develop reusable tools, adapters and configuration layers to support scalable enterprise onboarding.
• Collaborate with customer stakeholders (mainly within marketing, operations and engineering) to define requirements, surface edge cases and iterate in real time.
• Work closely with Gradial’s product and engineer teams to incorporate learnings from the field into our core roadmap.
• Contribute to internal technical documentation and implementation playbooks that accelerate future deployments.
• Own performance, reliability and maintainability for the solutions you ship, from backend architecture to customer UX.

What We're Looking For

• 3+ years of software engineering or technical implementation experience, ideally in customer-facing contexts.
• Proficiency in programming languages such as TypeScript or similar, with a strong understanding of APIs and systems integration.
• Ability to rapidly understand unfamiliar technical ecosystems (CMS, DAM, workflow tools) and build integration paths.
• Excellent communication skills. Confident translating for both technical and non-technical stakeholders.
• High ownership mindset with comfort operating independently, navigating ambiguity.
• Willingness to travel occasionally (<10%) for customer discovery, deployment and relationship building.

Nice to Have

• Experience working with enterprise customers; particularly in content, marketing or digital operations.
• Familiarity with LLMs, generative AI pipelines and agent-style automation frameworks.
• Background in consulting, technical solution engineering or internal tools engineering.

Compensation 

The salary range for this position is $130,000 – $210,000 annually. Final compensation will be determined based on factors such as experience, skills, and qualifications. In addition to base salary, this role may be eligible for performance-based bonuses and equity awards. Gradial offers a comprehensive benefits package, including medical, dental & vision insurance, 401K retirement plan, paid time off, paid sick leave and other employee wellness programs. 

Marketing at Brex

Marketing tells the story of Brex to the world. From acquisition to activation, we translate product value into business results. Our team spans Revenue, Product, and Brand Marketing, and works closely with nearly every function at Brex. We move fast, experiment often, and think deeply about customer behavior. If you want your creativity to drive growth and shape perception, this is the place.

What you’ll do

The Brex Marketing team is looking for an experienced Senior Marketing Operations Manager to own the systems, data infrastructure, and digital growth engine powering our Product-Led Growth (PLG) motion. This role is central to how Brex scales digital acquisition, optimizes self-serve onboarding flows, and unlocks marketing performance through automation, experimentation, and insights.

The ideal candidate is passionate about building a best-in-class marketing tech stack—including structuring event schemas, improving attribution, unlocking insights, and driving efficiency. This person is also excited about how AI and agentic workflows can transform our operational processes, improve personalization, accelerate experimentation velocity, and automate routine tasks. You will help define and execute our future-state marketing operations architecture, modernizing systems, processes, and data across paid, web, product, and lifecycle channels.

Where you’ll work

This role will be based in our New York City office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own and evolve the PLG martech ecosystem—including Twilio Segment, Google Analytics, Marketo, Sanity CMS, Salesforce, and paid-channel integrations—to ensure a best-in-class, scalable, and reliable infrastructure.
• Define and execute a future-state roadmap for PLG operations, leveraging AI-driven automation, agentic workflows, and scalable systems foundations.
• Build and optimize automated lifecycle and activation programs using AI-assisted segmentation, predictive scoring, and personalized content delivery.
• Partner with Web, Product, and Engineering teams to modernize event tracking frameworks, ensuring clean, structured, privacy-aligned data flows through Segment, GA, and in-product analytics.
• Support and scale experimentation by integrating event tracking, metadata, and insights with AI-enabled analysis and rapid test iteration.
• Collaborate with Paid Growth to ensure high-quality tagging, attribution, and channel measurement across Google Ads, LinkedIn Ads, Meta Ads, and Reddit Ads.
• Partner cross-functionally with CX, Operations, Sales, and Web teams to support chatbot and live chat experiences on Brex.com — including qualification logic, routing workflows, data capture, and integration with downstream teams. Serve as the Marketing Operations lead ensuring technical implementation, measurement, workflow orchestration, and operational governance, even in a co-owned model.
• Build dashboards and insights leveraging AI-enhanced analytics to monitor PLG health, funnel friction, conversion behavior, and growth loops.
• Identify opportunities to automate manual processes using Zapier, Segment, Marketo programs, and AI agents to improve speed, accuracy, and scale.
• Troubleshoot and resolve issues across systems (Segment, GA, Marketo, Salesforce), maintaining a high-quality data environment and rapid operational velocity.

Requirements

• 4+ years in Marketing Operations, Growth Operations, or Digital Systems roles supporting PLG or digital-first acquisition funnels.
• Hands-on experience with Segment, Google Analytics, Marketo, and event-based tracking frameworks.
• Strong analytical capabilities related to experimentation, attribution, and funnel performance measurement.
• Experience supporting paid acquisition workflows across Google, LinkedIn, Meta, and other digital channels.
• Experience partnering with cross-functional teams (CX, Operations, Sales, Web) to manage or enhance chatbot and/or live chat experiences—including qualification, routing, data models, and workflows—even when operational ownership is distributed across teams.
• Demonstrated experience driving operational efficiency and automation through workflow orchestration tools (Zapier, agentic AI systems, CDP-triggered workflows).
• Track record of evolving or modernizing a marketing tech stack toward a future-state architecture.
• Experience collaborating closely with Product, Web Engineering, and Data teams.

Bonus Points

• Experience at FinTech or SaaS companies with PLG or self-serve onboarding models.
• Experience using AI and automation to scale marketing workflows, such as generative personalization, predictive scoring, and automated experiment QA.
• Comfort building integrated workflows between CMS (Sanity) and acquisition tracking systems.
• Familiarity with customer journey analytics tools such as Amplitude, Mixpanel, or similar.
• Demonstrated ability to document architecture, propose long-term solutions, and operationalize complex systems with cross-functional partners.
• Understanding of digital identity verification steps and risk-aware conversion optimization.
• Familiarity with Lead-to-Product connective processes (where website signups eventually feed the GTM funnel).
• Knowledge of ABM or enterprise programs is a plus for hybrid funnel interactions.

Compensation

The expected salary range for this role is $134,696 - $168,370.  However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Marketing at Brex

Marketing tells the story of Brex to the world. From acquisition to activation, we translate product value into business results. Our team spans Revenue, Product, and Brand Marketing, and works closely with nearly every function at Brex. We move fast, experiment often, and think deeply about customer behavior. If you want your creativity to drive growth and shape perception, this is the place.

What you’ll do

The Brex Marketing team is looking for an experienced Senior Marketing Operations Manager to own the systems, data infrastructure, and digital growth engine powering our Product-Led Growth (PLG) motion. This role is central to how Brex scales digital acquisition, optimizes self-serve onboarding flows, and unlocks marketing performance through automation, experimentation, and insights.

The ideal candidate is passionate about building a best-in-class marketing tech stack—including structuring event schemas, improving attribution, unlocking insights, and driving efficiency. This person is also excited about how AI and agentic workflows can transform our operational processes, improve personalization, accelerate experimentation velocity, and automate routine tasks. You will help define and execute our future-state marketing operations architecture, modernizing systems, processes, and data across paid, web, product, and lifecycle channels.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own and evolve the PLG martech ecosystem—including Twilio Segment, Google Analytics, Marketo, Sanity CMS, Salesforce, and paid-channel integrations—to ensure a best-in-class, scalable, and reliable infrastructure.
• Define and execute a future-state roadmap for PLG operations, leveraging AI-driven automation, agentic workflows, and scalable systems foundations.
• Build and optimize automated lifecycle and activation programs using AI-assisted segmentation, predictive scoring, and personalized content delivery.
• Partner with Web, Product, and Engineering teams to modernize event tracking frameworks, ensuring clean, structured, privacy-aligned data flows through Segment, GA, and in-product analytics.
• Support and scale experimentation by integrating event tracking, metadata, and insights with AI-enabled analysis and rapid test iteration.
• Collaborate with Paid Growth to ensure high-quality tagging, attribution, and channel measurement across Google Ads, LinkedIn Ads, Meta Ads, and Reddit Ads.
• Partner cross-functionally with CX, Operations, Sales, and Web teams to support chatbot and live chat experiences on Brex.com — including qualification logic, routing workflows, data capture, and integration with downstream teams. Serve as the Marketing Operations lead ensuring technical implementation, measurement, workflow orchestration, and operational governance, even in a co-owned model.
• Build dashboards and insights leveraging AI-enhanced analytics to monitor PLG health, funnel friction, conversion behavior, and growth loops.
• Identify opportunities to automate manual processes using Zapier, Segment, Marketo programs, and AI agents to improve speed, accuracy, and scale.
• Troubleshoot and resolve issues across systems (Segment, GA, Marketo, Salesforce), maintaining a high-quality data environment and rapid operational velocity.

Requirements

• 4+ years in Marketing Operations, Growth Operations, or Digital Systems roles supporting PLG or digital-first acquisition funnels.
• Hands-on experience with Segment, Google Analytics, Marketo, and event-based tracking frameworks.
• Strong analytical capabilities related to experimentation, attribution, and funnel performance measurement.
• Experience supporting paid acquisition workflows across Google, LinkedIn, Meta, and other digital channels.
• Experience partnering with cross-functional teams (CX, Operations, Sales, Web) to manage or enhance chatbot and/or live chat experiences—including qualification, routing, data models, and workflows—even when operational ownership is distributed across teams.
• Demonstrated experience driving operational efficiency and automation through workflow orchestration tools (Zapier, agentic AI systems, CDP-triggered workflows).
• Track record of evolving or modernizing a marketing tech stack toward a future-state architecture.
• Experience collaborating closely with Product, Web Engineering, and Data teams.

Bonus Points

• Experience at FinTech or SaaS companies with PLG or self-serve onboarding models.
• Experience using AI and automation to scale marketing workflows, such as generative personalization, predictive scoring, and automated experiment QA.
• Comfort building integrated workflows between CMS (Sanity) and acquisition tracking systems.
• Familiarity with customer journey analytics tools such as Amplitude, Mixpanel, or similar.
• Demonstrated ability to document architecture, propose long-term solutions, and operationalize complex systems with cross-functional partners.
• Understanding of digital identity verification steps and risk-aware conversion optimization.
• Familiarity with Lead-to-Product connective processes (where website signups eventually feed the GTM funnel).
• Knowledge of ABM or enterprise programs is a plus for hybrid funnel interactions.

Compensation

The expected salary range for this role is $134,696 - $168,370.  However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Marketing at Brex

Marketing tells the story of Brex to the world. From acquisition to activation, we translate product value into business results. Our team spans Revenue, Product, and Brand Marketing, and works closely with nearly every function at Brex. We move fast, experiment often, and think deeply about customer behavior. If you want your creativity to drive growth and shape perception, this is the place.

What you’ll do

The Brex Marketing team is looking for an experienced Senior Marketing Operations Manager to own the systems, data infrastructure, and digital growth engine powering our Product-Led Growth (PLG) motion. This role is central to how Brex scales digital acquisition, optimizes self-serve onboarding flows, and unlocks marketing performance through automation, experimentation, and insights.

The ideal candidate is passionate about building a best-in-class marketing tech stack—including structuring event schemas, improving attribution, unlocking insights, and driving efficiency. This person is also excited about how AI and agentic workflows can transform our operational processes, improve personalization, accelerate experimentation velocity, and automate routine tasks. You will help define and execute our future-state marketing operations architecture, modernizing systems, processes, and data across paid, web, product, and lifecycle channels.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own and evolve the PLG martech ecosystem—including Twilio Segment, Google Analytics, Marketo, Sanity CMS, Salesforce, and paid-channel integrations—to ensure a best-in-class, scalable, and reliable infrastructure.
• Define and execute a future-state roadmap for PLG operations, leveraging AI-driven automation, agentic workflows, and scalable systems foundations.
• Build and optimize automated lifecycle and activation programs using AI-assisted segmentation, predictive scoring, and personalized content delivery.
• Partner with Web, Product, and Engineering teams to modernize event tracking frameworks, ensuring clean, structured, privacy-aligned data flows through Segment, GA, and in-product analytics.
• Support and scale experimentation by integrating event tracking, metadata, and insights with AI-enabled analysis and rapid test iteration.
• Collaborate with Paid Growth to ensure high-quality tagging, attribution, and channel measurement across Google Ads, LinkedIn Ads, Meta Ads, and Reddit Ads.
• Partner cross-functionally with CX, Operations, Sales, and Web teams to support chatbot and live chat experiences on Brex.com — including qualification logic, routing workflows, data capture, and integration with downstream teams. Serve as the Marketing Operations lead ensuring technical implementation, measurement, workflow orchestration, and operational governance, even in a co-owned model.
• Build dashboards and insights leveraging AI-enhanced analytics to monitor PLG health, funnel friction, conversion behavior, and growth loops.
• Identify opportunities to automate manual processes using Zapier, Segment, Marketo programs, and AI agents to improve speed, accuracy, and scale.
• Troubleshoot and resolve issues across systems (Segment, GA, Marketo, Salesforce), maintaining a high-quality data environment and rapid operational velocity.

Requirements

• 4+ years in Marketing Operations, Growth Operations, or Digital Systems roles supporting PLG or digital-first acquisition funnels.
• Hands-on experience with Segment, Google Analytics, Marketo, and event-based tracking frameworks.
• Strong analytical capabilities related to experimentation, attribution, and funnel performance measurement.
• Experience supporting paid acquisition workflows across Google, LinkedIn, Meta, and other digital channels.
• Experience partnering with cross-functional teams (CX, Operations, Sales, Web) to manage or enhance chatbot and/or live chat experiences—including qualification, routing, data models, and workflows—even when operational ownership is distributed across teams.
• Demonstrated experience driving operational efficiency and automation through workflow orchestration tools (Zapier, agentic AI systems, CDP-triggered workflows).
• Track record of evolving or modernizing a marketing tech stack toward a future-state architecture.
• Experience collaborating closely with Product, Web Engineering, and Data teams.

Bonus Points

• Experience at FinTech or SaaS companies with PLG or self-serve onboarding models.
• Experience using AI and automation to scale marketing workflows, such as generative personalization, predictive scoring, and automated experiment QA.
• Comfort building integrated workflows between CMS (Sanity) and acquisition tracking systems.
• Familiarity with customer journey analytics tools such as Amplitude, Mixpanel, or similar.
• Demonstrated ability to document architecture, propose long-term solutions, and operationalize complex systems with cross-functional partners.
• Understanding of digital identity verification steps and risk-aware conversion optimization.
• Familiarity with Lead-to-Product connective processes (where website signups eventually feed the GTM funnel).
• Knowledge of ABM or enterprise programs is a plus for hybrid funnel interactions.

Compensation

The expected salary range for this role is $134,696 - $168,370.  However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Build AI that matters. We ship production GenAI apps for confidential federal programs across defense, national security, public safety, civilian, and military health where reliability, privacy, and safety aren’t optional. AFS is a technology company within global Accenture and a Glassdoor Top 100 Best Place to Work. You’ll join a collaborative, inclusive community with handson growth, certifications, and industry training. We ship in weeks, not quarters, and measure success with latency, reliability, safety, and cost. 

Confidentiality matters: We don’t disclose program details publicly. If you advance, we’ll share specifics during the process. 

Role Overview 

You’ll turn mission needs into secure, reliable, and scalable GenAI applications no model training required. This is a hands-on role across agentic workflows, RAG, prompt/policy design, LLM evaluation, and platform integration. You’ll own the end-to-end path from use case evaluation → production deployment → operational excellence, partnering with product, security, data, and SRE to ship features safely and at scale. 

What You’ll Do (Day to Day) 

• Design & ship mission grade GenAI: Build agentic workflows and RAG systems tailored to mission data and environments; target low hallucination, tight p95 latency, and predictable cost. 

• Agent frameworks & orchestration: Apply patterns from LangChain/LlamaIndex/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies. 

• Platform integration (no model training): Implement with AWS Bedrock, Azure OpenAI, Google Vertex AI, Amazon Kendra, and managed services (e.g., Document AI, Gemini, Gemma). 

• LLM selection & evaluation: Compare models for quality, safety, latency, cost; author/test prompts & policies; deploy with observability and safe rollback/fallback. 

• RAG done right: Build retrieval pipelines & vector search (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise. 

• Production rigor: Instrument metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails. 

• SRE & FinOps for AI: Define SLIs/SLOs (quality/latency/safety/cost), run on call and postmortems, reduce MTTR; meter usage and optimize token/spend. 

• Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off projects. 

• Operate in real world constraints: Deliver into hybrid, restricted, or air gapped environments with Zero Trust principles and audit ready controls. 

You'll Thrive Here If you have 

• End-to-end ownership of production systems: integration → deployment → observability → incident response. 

• Hands-on experience with LLMs, transformer based apps, and RAG in production. 

• Strong Python 

• Experience with vector search and retrieval (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma) and grounding AI in enterprise/mission data. 

• U.S. Citizenship 

Nice to Have 

• Integration with leading cloud AI services or on prem inference stacks  

• Background in LLM evaluation, prompt authoring/testing, A/B experimentation, and LLM Ops. 

• Responsible AI expertise (privacy, security, bias, transparency, human in the loop) and data governance. 

• Experience implementing tool using agents for API integration and external data access. 

• Containerization & orchestration (Docker, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell). 

• Prior work in regulated/secure environments (e.g., ATO, STIGs, Zero Trust) with fast shipping. 

• Familiarity with NVIDIA AI Foundations, OpenAI ChatGPT, and AI assisted dev tools (Cursor, Windsurf, Claude). 

• Contributions to internal frameworks or opensource; mentorship of engineers. 

• Clear communication with engineers, PMs, and security/compliance stakeholders. 

ML Postdoc Researcher - Healthcare AI Innovation

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture.  Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program. #LI-remote

About Truveta 

Truveta is transforming healthcare by enabling researchers, clinicians, and life sciences organizations to learn from one of the most comprehensive collections of de-identified patient data in the United States. With access to longitudinal electronic health record (EHR) data from over 120 million patients (which represents over a third of the US population), we are uniquely positioned to drive breakthroughs in clinical research and improve patient outcomes. 

This Opportunity

We are seeking a highly motivated Postdoctoral Researcher to explore and develop novel applications of cutting-edge AI/ML technologies on large-scale real-world clinical data. 

This role is designed for recent PhD graduates who are passionate about pushing the boundaries of machine learning in healthcare. You will work at the intersection of machine learning, clinical data, and biomedical science, identifying new opportunities where modern AI can unlock insights that were previously out of reach. 

A key expectation is not just execution—but imagination: the ability to envision and prototype entirely new ways to use rich patient data to solve meaningful healthcare problems. 

Who You Are

• Curious and imaginative: You naturally think beyond existing solutions and ask “what hasn’t been done yet?”
• Impact-driven: You care about applying research to real-world healthcare problems
• Comfortable with ambiguity: You thrive in open-ended environments where defining the problem is part of the job
• Collaborative: You enjoy working across domains and learning from experts in different fields 

What You'll Do

• Innovate: Identify and propose novel, high-impact applications of AI/ML using large-scale EHR data
• Research & Prototype: Design, develop, and evaluate state-of-the-art models (e.g., foundation models, multimodal learning, causal ML, generative AI)
• Work Across Modalities: Integrate structured and unstructured EHR data with emerging data types such as genomics, imaging, and clinical notes
• Collaborate Cross-Functionally: Partner with clinicians, data scientists, and product teams to translate research ideas into real-world solutions
• Publish & Share: Contribute to top-tier conferences/journals and represent Truveta in the research community
• Explore the Unknown: Proactively identify problems that have not yet been addressed and define new research directions 

What We're Looking For

Basic Qualifications

• • Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
  • Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
  • Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
  • Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
  • Deliver the next generation of innovation in trustworthy healthcare.

Preferred Qualifications

• • Experience with healthcare data (EHRs, claims, clinical notes) or biomedical data (genomics, imaging)
  • Familiarity with cutting-edge areas such as: 
  • Foundation models / LLMs in healthcare
  • Multimodal learning
  • Causal inference
  • Representation learning on longitudinal data
  • Track record of publications in top-tier ML or healthcare venues (e.g., NeurIPS, ICML, ICLR, MLHC, AMIA)
  • Ability to work across disciplines and communicate with both technical and clinical stakeholders 

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together. 

We offer: 

• Competitive compensation
• Company-issued laptop and equipment
• Opportunities for future full-time positions
• The range for this position is $50-$60 per hour

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

ML PhD Intern - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture.  Participation in the internship program requires that you are physically present in the United States for the duration of the internship. #LI-remote

Who We Need 

We are seeking a highly motivated and talented Machine Learning PhD Intern to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

Internship Details

Our Research PhD Internship is designed for candidates who have finished their classes and are working only on research work to complete their PhD. Candidates must be within 1 year of their graduation date from their PhD program. Candidates are expected to demonstrate both independence in defining their research strategy within a domain as well as an ability to apply innovative solutions to our products. Our internships are designed to be a minimum of 10 weeks with the opportunity to extend beyond the initially agreed term based on the company’s needs and the candidate’s desires.

This Opportunity

We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

In this role, you will:

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy healthcare.

Key Qualifications

• Currently pursuing a Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI
• Strong theoretical and practical background in NLP including experience with state-of-the-art architectures
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems
• Strong communication skills and the ability to work effectively in a collaborative research environment

Preferred Qualifications

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models
• Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques
• Familiarity with training multi-modal foundation models
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments
• A track record of publications and contributions to the machine learning and natural language processing communities

This internship opportunity offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of Saving Lives with Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the healthcare domain. Join us and make a significant impact on the future of healthcare and patient well-being.

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together. 

We offer: 

• Competitive compensation
• Company-issued laptop and equipment
• Opportunities for future full-time positions
• The hourly pay for this position is $45

Truveta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Senior Clinical Data Scientist - Applied Intelligence Solutions

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Truveta was born in the Pacific Northwest, but we have employees who live across the country.  Our team enjoys the flexibility of a hybrid model and working from anywhere.  In person attendance is required at least once per year for an onsite meeting. 

For overall team productivity, we optimize meeting hours in the pacific time zone. We avoid scheduling recurring meetings that start after 3pm PT, however, ad hoc meetings occur between 8am-6pm Pacific time. #LI-remote

Who We Need 

Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. 

This Opportunity 

We are seeking a Senior Clinical Data Scientist to join the Catalysts team, focused on applied intelligence solutions for Truveta.

This role focuses on building the concrete intelligence assets that intelligence uses to solve defined healthcare problems correctly and safely. You will work on concrete problem types such as safety monitoring, cohort feasibility, HEOR analyses, clinical trial workflows, and operational oversight, and be responsible for directly creating the knowledge assets, examples, and guardrails that intelligence uses to support these problems effectively and safely. 

A core part of the role is creating and maintaining practical intelligence assets that intelligence directly uses to support specific, repeatable solutions. These assets are contributed into a shared knowledge base maintained by the broader Catalysts team. 

You will also influence how intelligence consumes and applies knowledge by producing clear, reusable assets that translate complex technical and domain concepts into forms usable by both intelligence systems and non technical stakeholders. 

Out of scope: This role is not focused on model training, infrastructure, or large scale implementation. You are expected to be technically fluent and able to prototype, while deeper execution is handled collaboratively with peers who specialize in speed and scale. 

Responsibilities

• Intelligence solution construction: Independently build small scale, concrete intelligence solutions for specific healthcare problems by creating the required knowledge assets, examples, reference analyses, and guardrails that allow intelligence to answer the right questions and respect clear boundaries, within current platform capabilities.
• Domain problem breakdown: Break down healthcare problems in areas such as clinical research, HEOR, and clinical trials into the concrete assumptions, decision points, and data considerations that intelligence needs to handle correctly.
• Knowledge and guidance definition: Create and maintain the domain knowledge, guidelines, templates, and decision logic that intelligence systems need in order to perform effectively in each problem domain.
• Agent and workflow shaping: Shape how intelligence agents operate at a practical level by defining task breakdowns, decision logic, and required knowledge, working within current platform constraints.
• Knowledge extraction and transformation: Work with domain experts and users to extract assumptions, heuristics, and expertise, and convert them into structured inputs that intelligence systems can reliably consume.
• Generative AI reasoning: Apply an understanding of how generative AI systems retrieve and reason over knowledge to improve correctness, safety, and consistency of intelligence outputs, using concrete examples and test questions.
• Validation and guardrails: Define and validate constraints, exclusions, and limitations to ensure intelligence outputs are appropriate, trustworthy, and aligned with real world healthcare use.
• Collaboration and facilitation: Work closely with colleagues across the Catalysts team, contributing domain expertise, intelligence design, and reusable assets into a shared knowledge base, and collaborating as peers on intelligence solutions rather than owning a separate execution pipeline. 

Required Skills

• Education: Bachelor’s degree or equivalent experience in a quantitative or technical field such as computer science, data science, statistics, engineering, or a related discipline.
• Applied intelligence and LLM expertise: Strong understanding of how large language models consume, retrieve, and reason over knowledge, and how to structure information so it can be used efficiently and reliably by intelligence systems.
• Healthcare domain knowledge: Solid understanding of healthcare problem spaces such as clinical research, HEOR, clinical trials, and healthcare operations, and the types of questions and decisions users need support with.
• Generative AI fluency: Hands on experience using generative AI tools to synthesize, generate, and refine knowledge assets including guidance, templates, prompts, and structured explanations.
• Applied solution design: Ability to design and prototype applied intelligence solutions for specific problem types by combining domain knowledge, templates, prompts, guardrails, and workflows.
• Technical fluency: Comfortable writing and reviewing production quality analysis code (e.g., SQL, Python, or R) to prototype analyses, validate logic, and create reusable examples that intelligence and teammates can reuse. Deep engineering expertise is not required, but hands on technical fluency is expected.
• Knowledge creation and translation: Create clear, reusable intelligence assets by synthesizing expert input or authoring directly, translate technical and domain specific concepts into guidance that is understandable and actionable for a wide range of audiences, and explicitly define exclusions and limitations where intelligence should not provide answers. 

Preferred Qualifications

• Healthcare and EHR exposure: Experience working with healthcare or EHR data, including awareness of common data quality issues, biases, and clinical context.
• Decision support systems: Experience designing, evaluating, or contributing to decision support systems, recommendations, or intelligent assistants.
• Applied research background: Background in product analytics, applied research, or applied machine learning in support of real world decision making.
• Advanced technical depth: Experience building more complex analytical workflows, reusable code libraries, or data products that others rely on, even if this is not the primary focus of the role.
• Knowledge formalization: Experience translating expert knowledge into structured guidance, documentation, schemas, or training materials.
• Teaching and enablement: Teaching, mentoring, or enablement experience with analysts, researchers, or cross functional teams. 

Why Truveta?   

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together.  

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $155,000 to $170,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

ML Postdoc Researcher - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture.  Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program. #LI-remote

Who We Need 

We are seeking a highly motivated and talented Machine Learning Postdoctoral Researcher to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

Program Details

Our Postdoctoral Research program is designed for candidates who have completed their PhD within the last two years and worked in their area of expertise since graduation as a postdoc, professor, or industry researcher/scientist. Candidates are expected to demonstrate both independence in defining their research strategy within a domain as well as an ability to apply innovative solutions to our products. Our postdoc research programs are designed to be a minimum of 3 months and a maximum of 12 months, with the opportunity to extend beyond the initially agreed term based on the company’s needs and the candidate’s desires.

This Opportunity

We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

In this role, you will:

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy healthcare.

Key Qualifications

• Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI
• Strong theoretical and practical background in NLP including experience with state-of-the-art architectures
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems
• Strong communication skills and the ability to work effectively in a collaborative research environment

Preferred Qualifications

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models
• Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques
• Familiarity with training multi-modal foundation models
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments
• A track record of publications and contributions to the machine learning and natural language processing communities

This postdoctoral research program offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of Saving Lives with Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the healthcare domain. Join us and make a significant impact on the future of healthcare and patient well-being.

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together. 

We offer: 

• Competitive compensation
• Company-issued laptop and equipment
• Opportunities for future full-time positions
• The range for this position is $50-$60 per hour

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Machine Learning Engineer - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

This position is based out of our headquarters in the Greater Seattle area.  #LI-hybrid

Who We Need 

Truveta is building a diverse and inclusive team to tackle complex health and technical challenges. We are seeking enthusiastic new graduates who are problem-solvers, collaborative teammates, and eager to make a difference in healthcare. If you’re excited about purposeful work, joining a mission-driven team, and launching your career in a supportive environment, Truveta could be the perfect place to start.

This Opportunity 

We are looking for a Machine Learning Engineer with a deep background in generative AI, large language models (LLMs), and reinforcement learning techniques to build the next generation of AI systems for trustworthy healthcare. This role offers a unique opportunity to build foundational models trained on vast clinical data and drive innovation in a highly meaningful domain.

Responsibilities

• Lead the development, training, and deployment of large language and multimodal foundation models tailored to clinical and biomedical domains.
• apply and refine state-of-the-art techniques such as supervised fine-tuning (SFT), reinforcement learning-based methods (e.g., RLHF, RLVR), parameter-efficient fine-tuning (PEFT), prompt tuning, and retrieval-augmented generation (RAG).
• Collaborate cross-functionally with researchers, clinicians, and engineers to design ML-driven solutions that improve healthcare delivery and outcomes.
• Build scalable infrastructure for distributed training of large models (TPU/GPU clusters, multi-node orchestration).
• Design and evaluate models for robustness, bias mitigation, factual consistency, and explainability in healthcare contexts.
• Stay current with the latest research in generative AI and contribute back to the community through publications and open-source initiatives.

Minimum Qualifications

• 6+ years of experience in software engineering or machine learning (3+ years with a PhD).
• Experience designing and training LLMs or large-scale generative models (e.g., GPT, PaLM, LLaMA, Claude, Gemma).
• Deep expertise in NLP, sequence modeling, and transformer architectures.
• Proficient in Python and ML libraries such as PyTorch or TensorFlow; strong engineering skills in building scalable ML pipelines.
• Experience with RL-based fine-tuning (e.g., Reinforcement Learning from Human Feedback) and evaluation of generative systems.
• Proven ability to lead technical projects and collaborate across teams.
• Bachelor's degree in Computer Science, Engineering, or a related technical field

Preferred Qualifications

• PhD or equivalent experience in Machine Learning, NLP, AI, or a related field.
• Experience in healthcare, biomedical informatics, or clinical data modeling.
• Familiarity with multi-modal foundation models (e.g., text-image, text-structured data) and cross-modal alignment techniques.
• Hands-on experience with vector databases, semantic search, and retrieval-based generation
• Publications in top-tier ML conferences (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.).
• Experience building trustworthy AI systems and applying model interpretability, fairness, and safety frameworks.

Why Truveta?

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional, and everything in between. Join us as we build an amazing company together.

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $155,000 to $175,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

Our base salary range is $170,000 - $220,000, and in addition we have generous bonus plans to provide a competitive compensation package. 

Who We Are: 

We are a non-profit AI institute, focused on developing foundational AI research and innovation to deliver real-world impact through large-scale open models, data, and artifacts (e.g., Olmo, Tulu, Molmo).   We unite the best and brightest scientific and engineering minds to explore the potential of truly open AI. Through  our efforts, including the pioneering Olmo releases, we endeavor to empower academics, researchers, and AI developers more broadly to advance language models and generative AI models. Through close collaboration, we rapidly identify, define, and act on the most exciting and promising new ideas in AI.  

Our team engages in a broad range of AI research, including pre-training and post-training language models, curating data to enhance AI across different modalities, and developing novel methodologies to push the field forward. We study and evaluate AI models both theoretically and empirically, aiming to advance their capabilities. Additionally, we create impactful real-world applications, such as in scientific synthesis. Our goal is to develop state-of-the-art models that excel in scientific discovery, reasoning, and factual recall.

Who You Are: 

You are a talented, hands-on engineer who thrives in a fast-paced environment, is self-directed, a team player, and knows how to get things done. You have a deep knowledge of Python, infrastructure, and a strong understanding of modern deep learning, natural language processing, language models, and the inner workings of the transformer architecture. You can translate high-level goals into concrete research and implementation steps, set an approach, follow through, and present results. When it’s time to explain your ideas, you bring clarity to complex technical issues. You use these skills to create real-world benefits for researchers and other practitioners, and you are excited to help advance our effort to create the best-performing open AI model.

Your Next Challenge:

You will be a part of the core team of research and machine learning engineers working on the infrastructure, architecture, modeling and training of Olmo (Open Language Model) at all stages: pre-training, mid-training, post-training and all emerging paradigms. In this role you will be owning the design and implementation of the systems that train these models. You will be responsible for building scalable machine learning pipelines as we push the boundaries of large language modeling research. You will be collaborating with colleagues inside and outside your own team, but you are responsible for a feature or experiment from start to finish, from conception to implementation.

The essential functions include, but are not limited to the following:

• Building infrastructure to facilitate the next generation of LLM research
• Optimizing training and inference for language models
• Triaging between experiments and executing on the most impactful
• Supporting and collaborating with an open-source community
• Bridging the gap between cutting-edge research and a widely adopted product
• Bringing software engineering best practices to a research environment
• Releasing your contributions back to the broader community in the form of open source software, model releases, and additions to Ai2’s public API and open research datasets, as well as technical reports

What You’ll Need: 

• Expertise at building ML infrastructure - having 4+ years of industry experience building infrastructure that handles data preprocessing/transformation and model training, evaluation, inference, and deployment
• Deep experience in the complete model development cycle, including data set construction, training, tuning, evaluation, performance profiling, and monitoring
• Knowledge of modern deep learning and natural language processing techniques
• Strong software engineering skills, particularly around building performant systems and debugging
• At-home with hands-on programming – must have experience with Python and PyTorch/Jax/Tensorflow. We expect you to be the kind of engineer who can pick up a new programming language, library, or API as needed without it being a big deal.
• Familiarity working with cloud compute resources (e.g. AWS) and containerization (e.g. Docker)
• Strong collaboration and communication skills - our environment is small and collaborative, and we'd like you to thrive while working closely with others, sometimes with complementary skills/perspectives

Bonus qualifications:

• Advanced degree in Data Science/CS/EE/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent engineering experience
• Contributions to open-source ML or research libraries (e.g. spaCy, AllenNLP, transformers)
• Experience successfully operating models at scale in a production setting
• Experience in HPC settings
• Curiosity about AI research

Education:

• BS or MSc in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Must be able to remain in a stationary position for long periods of time.
• The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.
• The ability to observe details at close range.
• Can work under deadlines.

A Little More About Ai2:

The Allen Institute for Artificial Intelligence is a non-profit research institute in Seattle founded by Paul Allen. The core mission of Ai2 is to contribute to humanity through high-impact research in artificial intelligence. 

In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:

• We are a learning organization – because everything Ai2 does is ground-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers. 
• We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
• We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
• We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
• We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
• We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
• We are friendly– chances are you will like every one of the 200+ people who work here. We do. 

Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links. 

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at recruiting@allenai.org.

Benefits:

• Team members and their families are covered by medical, dental, vision, basic life insurance, basic accidental death and dismemberment insurance, short-term disability, long-term disability, and an employee assistance program.
• Team members are able to enroll in our voluntary life insurance program, our voluntary accidental death and dismemberment program, our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
• Team members are able to enroll in our company’s 401k plan.
• Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
• Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
• Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship.