We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud infrastructure challenges in the fast-growing AI/ML space. This is a high-impact position designed to be the "technical tip of the spear" for our most strategic AI-Native (ANE) customers.

As an FDE, you will sit at the intersection of Product Engineering and Customer Implementation. You will be embedded directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

You will build the tools, migration scripts, and AI starter kits that don't just solve one customer's problem, but scale the entire DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time-to-inference" in production at scale and serve as a critical feedback loop, ensuring our product roadmap is informed by the world's most demanding AI workloads.

What you’ll do:

• Embedded Customer Engineering: Partner deeply with strategic ANEs to manage complex migrations, build production-ready PoCs, and execute hands-on application builds on our GPU infrastructure.
• Build Scalable Assets & Tooling: Operationalize field learning by building migration planners, reusable systems, benchmarking frameworks, model optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) that standardize how AI workloads are deployed and tuned across DigitalOcean.
• Develop AI "Starter Kits": Create pre-built GenAI agents, solution templates, and notebooks (e.g., LangGraph, CrewAI) tailored to popular and advanced business needs.
• Drive the Product Roadmap: Act as the frontline technical voice for CPTO, surfacing architectural gaps and edge cases to inform core product development. Transition field-built tools into native product features.
• New Tech Validation: Lead the early testing and integration of emerging AI frameworks to ensure a first-class developer experience on DigitalOcean.
• Partner & GTM Enablement: Co-develop delivery frameworks with Strategic and Technical partners to enable repeatable, high-quality deployments at scale.
• Market Leadership: Produce field-tested demo kits and deployment guides that support new product releases with practical, validated assets.

Key Metrics

• Customer Adoption: Number of high-impact production workloads landed; reduction in average "time-to-production"; and Pilot-to-Production conversion rates.
• Asset & Tooling Delivery: Number of reusable tools (agents, scripts, playbooks) delivered per quarter and their subsequent adoption rate by the crossfunctional teams and customers.
• Field Enablement & Scale: Measured by the successful handoff and execution of FDE-defined deployment patterns to technical partners and the internal adoption rate of FDE playbooks across all customer-facing technical teams.
• Product Influence: Number of roadmap features or architectural changes directly attributed to FDE feedback and validated customer hypotheses.

What You’ll Add to DigitalOcean:

• AI/ML Architecture & Domain Expertise: Significant experience in the AI/ML lifecycle, specifically hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular. You have a deep understanding of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Distributed Systems & Infrastructure Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
• High-Performance Inference & Hardware Optimization: Hands-on experience with distributed inference serving frameworks (e.g., llm-d, NVIDIA Dynamo, or Ray Serve). You understand GPU-level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
• Software Engineering Foundation: Strong production coding skills in Python or Go with the ability to build high-quality tools, automation, and internal assets.
• Data-Driven Performance Insight: Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
• Consultative Execution: Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high-stakes technical migrations.

Preferred

• Experience with emerging AI orchestration frameworks like LangGraph, CrewAI, or LlamaIndex.
• A background in technical consulting or "Forward Deployed" roles at high-growth AI or infrastructure companies.
• Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
• Active contributor to open-source AI projects or technical communities.

Compensation Range: 

• $195,000 - $239,000

*This is a remote role

JR: 2026-7748

#LI-Remote

We want people who are passionate about troubleshooting complex problems with systems, networking and storage at scale.

We are looking for a seasoned system administrator to help us keep the cloud running smoothly. Reporting to the manager of Cloud Operations, the GPU Operations Engineer monitors and provides first-response to all cloud health issues that impact, or could potentially impact, customer experience - internal or external. You will interface with teams across the organization to research and troubleshoot issues from single droplets to cloud-wide disturbances. Our workweek spans five days, and that may involve working on weekends.

What You'll Be Doing: 

• Ensuring maximum uptime for our global infrastructure
• Automating processes and building tools to improve operational efficiency
• Coordinating operational work across teams to improve the platform with minimal impact

What You'll Add to DigitalOcean:

• Solid experience with Linux operating systems or Networking and day to day upkeep
• Familiarity with virtualization technologies and troubleshooting virtual machine instances
• Familiarity with containerization technologies and troubleshooting containers
• Familiarity with IPv4 Networking and troubleshooting (CCNA equivalent)
• Basic storage concepts and technologies
• Experience with monitoring systems and incident management
• Experience scripting in one or more of the following languages: Bash, Python, or Go
• Experience with GPU hardware or AI/ML, and Kubernetes
• A passion for good documentation and open communication
• Proven ability to learn!

Compensation Range: 

• $107,000 - $134,000

*This is a remote role

JR: 2026-7423

#LI-Remote

Staff GenAI Research Scientist - Retrieval

P-1214

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description 

As a Staff Research Scientist on the Enterprise Agents team, you will be responsible for keeping up with the latest developments in Agent Context, Information Retrieval, Knowledge Assistants, RAG, Embeddings, and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Staff Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on Information Retrieval for reusable Agent components, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches.
• Drive research and technical strategy across enterprise retrieval and search, including workspace search, vector search.
• Drive algorithmic innovations for Retrieval within Large Language Models. 
• Experience with Agent Benchmarks for retrieval, text-embeddings and LLM Data Quality. 

What We Look for

• 5+ years of 
• PhD in Computer Science or related field with strong foundations in Natural Language Processing and Information Retrieval 
• Developing and implementing methods that extend and improve model capabilities, reliability, and safety. 
• Strong preference for candidates with first-author publications at top ML/systems conferences (EMNLP, ICLR, ACL, NeurIPs) focused on optimization or efficiency.

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description 

As a Sr. Research Scientist on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Sr. Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches
• Drive algorithmic innovations for large-scale neural network training or inference (e.g., novel optimizers, low-precision techniques, model adaptation methods)
• Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.

What We Look for

• MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
• Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation
• Strong preference for candidates with first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.

MaintainX is the world's leading AI-powered maintenance and asset management platform, serving 13,000+ customers including Duracell, Shell, Cintas, and Brenntag. We raised $150M in Series D funding led by Bessemer Venture Partners and Bain Capital Ventures, bringing our total funding to $254M. We were named to the Forbes 2025 Cloud 100, the definitive ranking of the top 100 private cloud companies in the world.

We are seeking a Principal Technical Program Manager to drive our most complex, cross-functional engineering initiatives. You'll own a portfolio of programs spanning Core product, AI/ML, Platform, Infrastructure, and Enterprise — operating as a peer to our senior engineering leaders and influencing without direct authority. This is a senior individual contributor role.

What You’ll Do

• Own end-to-end execution of company-critical programs that span Core product, AI/ML, Platform, Infrastructure, and Enterprise teams.
• Lead design and delivery of highly complex initiatives in ambiguous or new technology areas; make tradeoffs across scope, quality, timing, and architectural debt.
• Establish OKRs, KPIs, and the operating rhythm (planning, reviews, retros, exec updates) that keep a fully distributed engineering org aligned and shipping.
• Surface cross-team risks early, provide escalation management, and steer teams away from prior failure patterns.
• Create scalable mechanisms and methodologies that hold up as the engineering org grows.
• Author strategy narratives, program plans, and exec memos; present to leaders two and three levels above with the clarity expected at the principal level.

About You

• 10+ years managing technical programs across cross-functional engineering teams.
• 3+ years operating at a principal or staff level driving multi-org programs.
• Experience leading complex programs in at least three of: infrastructure or platform, AI/ML, consumer or frontline products, and enterprise/B2B.
• Experience defining KPIs and SLAs and reporting program outcomes to executive leadership.

Preferred Qualifications

• Experience shipping AI/ML-powered products or working with foundation models.
• Experience scaling platform or infrastructure teams through hypergrowth.
• Experience supporting an upmarket motion to Fortune 5000 customers.
• Track record authoring strategy narratives and exec memos that drive decisions.
• Demonstrated track record of using AI tools (Claude, ChatGPT, etc) to scale your own throughput as a TPM.

What’s In It for You

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take-what-you-need PTO and flexible work culture.
• A Work Culture where:
  • You'll work alongside folks across the globe that reflect the MaintainX values, Smart Humble Optimist.
  • We believe in meritocracy, where ideas and effort are publicly celebrated.

About Us

Our mission is to make the lives of blue-collar workers easier worldwide by creating software that meets their needs and realities. Our product is truly life-changing for 80% of the workforce that doesn’t work behind a desk and needs enterprise-grade software at their fingertips.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

#LI-Remote

Corporate Counsel 

Location

San Francisco Presidio HQ or Bellevue

About the Role

Armada is seeking a pragmatic, business-minded Corporate Counsel to join our Legal team, reporting directly to the Head of Legal. This is a high-impact role for an attorney who thrives in fast-moving environments and wants broad exposure across corporate governance, strategic transactions, commercial matters, and operational legal support.

As Corporate Counsel, you will partner closely with leadership and cross-functional stakeholders across Finance, People, Operations, Product, GTM, and Engineering to help Armada scale responsibly and efficiently. You will support a wide range of legal initiatives, including corporate governance, strategic transactions, entity management, and day-to-day corporate legal operations.

This role is ideal for an attorney who combines strong legal fundamentals with sound business judgment, enjoys operating with autonomy, and is excited to build scalable processes at a rapidly growing technology company.

What You’ll Do

• Support corporate governance matters, including board and committee materials, resolutions, minutes, consents, and maintenance of corporate records across the corporate group.
• Assist with strategic transactions, including mergers and acquisitions, investments, financing transactions, strategic partnerships, and related diligence and documentation.
• Support subsidiary management and entity governance across domestic and international jurisdictions, including formations, qualifications, annual filings, and compliance obligations; coordinate with local counsel to ensure entities remain in good standing.
• Help manage equity-related matters, including equity award documentation, cap table coordination, 409A processes, and support for employee equity programs.
• Assist with corporate policies, compliance initiatives, and risk management processes as Armada scales globally, including policies governing insider trading, conflicts of interest, and corporate conduct.
• Partner cross-functionally with Finance, People, Operations, and business leaders on corporate and operational legal matters.
• Work closely with outside counsel on corporate, employment, compliance, and transactional matters as needed.
• Build and improve legal templates, playbooks, workflows, and operational processes to drive efficiency and scalability.
• Provide practical, business-oriented legal advice that balances risk management with execution velocity.
• Contribute across a wide variety of legal and operational projects in a collaborative, high-ownership environment — Armada moves fast and priorities shift; flexibility and good judgment are essential.

What We’re Looking For

• J.D. from an accredited law school and active membership in at least one U.S. state bar
• 4–7 years of relevant legal experience at a top law firm and/or in-house legal department
• Strong foundation in corporate law, commercial transactions, and corporate governance
• Experience supporting strategic transactions, financing matters, or M&A is a plus
• Exceptional drafting, negotiation, organizational, and project management skills
• Ability to simplify complex legal concepts into practical guidance for business stakeholders
• Comfortable operating independently in a fast-paced, evolving environment with shifting priorities
• Strong attention to detail with a proactive, solutions-oriented mindset
• Collaborative team player with excellent judgment and communication skills
• Excited to work in a high-growth environment where no task is too big or too small
• Interest in infrastructure, AI, emerging technologies, or high-growth technology businesses is a plus

Why Join Armada

• Opportunity to help shape the legal foundation of a rapidly scaling technology company
• Broad exposure to strategic, operational, and commercial legal matters
• High visibility and partnership with company leadership
• Collaborative, mission-driven culture with meaningful ownership and impact
• Competitive compensation, equity, and benefits package

THE ROLE

As an Applied Research Engineer at Snorkel AI, you will own the infrastructure that powers our model training and evaluation work. This is a hands-on role where you will build and operate GPU cluster infrastructure, training pipelines, and the tooling that allows our research and engineering teams to run experiments reliably and at scale. You will work closely with research scientists and engineers, translating training requirements into robust, reproducible systems—and proactively removing infrastructure blockers before they slow down the work that matters most.

Snorkel AI operates in a fast-paced, high-impact environment. We are looking for someone who takes pride in operational excellence, loves solving complex distributed systems problems, and thrives when given real ownership.

Location: Redwood City or San Francisco — OR REMOTE

MAIN RESPONSIBILITIES

• Set up and manage GPU cluster infrastructure on major cloud providers (e.g., AWS HyperPod) for distributed model training, including networking, provisioning, and cost tracking.
• Build and operate job orchestration and scheduling systems (e.g., Kubernetes, Slurm, or cloud-native equivalents) to reliably launch and manage training, rollout, and evaluation jobs across multi-node clusters.
• Integrate and maintain ML training frameworks and post-training pipelines, ensuring they run stably and reproducibly at scale.
• Set up and maintain experiment tracking, dataset versioning, and model artifact management to support fast iteration.
• Monitor and optimize cluster health, inter-node communication, and resource utilization; implement fault tolerance and auto-recovery so long-running jobs survive node failures.
• Work closely with research scientists and ML engineers to understand requirements, unblock experiments, and evolve infrastructure as our training workloads needs change.

PREFERRED QUALIFICATIONS

• Hands-on experience managing GPU clusters on major cloud providers, including provisioning, network configuration, and cost management.
• Experience with distributed compute orchestration tools such as Kubernetes, Slurm, or equivalent cluster management systems.
• Working knowledge of distributed training concepts: parallelism strategies, memory optimization techniques, and inter-node communication.
• Experience with setting up, managing, and integrating ML experiment tracking and data/model versioning tools..
• Strong Python proficiency and solid software engineering fundamentals such as version control, modular design, and automation.
• Ability to work in a fast-moving, iterative environment and take end-to-end ownership of ambiguous infrastructure problems.
• Hands-on experience with post-training workflows such as supervised fine-tuning (SFT) or reinforcement learning (RLHF, GRPO, or similar) is a strong plus, but not required.

This role is a great fit for engineers who love building reliable systems close to the frontier of AI research. We welcome applicants from a wide range of backgrounds—whether your experience comes from industry, research labs, or direct hands-on work with distributed infrastructure at scale.

BE YOUR BEST AT SNORKEL

Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.

Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Okta’s Strategic Sourcing and Procurement (SS&P) team is looking for an experienced Category Manager to join our team to co-lead global sourcing activities for indirect services. This includes leading projects and contract negotiations for various spend categories such as Professional Services (Consulting, Finance & Legal), Facilities, and HR. 

In this role, you will be a trusted partner to our stakeholders, guiding them throughout the entire sourcing process. You will be responsible for developing and executing the sourcing strategy for the Professional Services and HR categories, leading complex negotiations, and driving cost-saving initiatives while maintaining service quality.

We are looking for a proactive, organized, and collaborative individual who works well in a fast-paced environment. This role will report to the Manager, Strategic Sourcing -  Indirect. The is a hybrid role (2 days a week in office) and must be based in either  Bellevue, WA, or the San Francisco Bay Area.

Key Responsibilities:

• Category Strategy & Planning: Develop and execute proactive sourcing strategies for the Professional Services, Facilities and/or HR categories, working closely with functional groups to understand their long-term needs and deliver tangible value.
• Sourcing & Project Management: Manage the entire lifecycle of sourcing projects from end-to-end, including conducting RFIs, RFPs, and market assessments to lead supplier selection activities.
• Contract Negotiation: Lead commercial term negotiations for project-level agreements (Statements of Work, Order Forms) and partner with Legal on Master Service Agreements (MSAs) or various Exhibits, ensuring favorable terms and compliance.
• Cost Optimization: Identify and implement cost-saving opportunities through strategic negotiations and process improvements. Develop and track KPIs to measure savings and value.
• Stakeholder Partnership:  Build strong relationships with stakeholders to understand their objectives and align procurement initiatives with their business requirements.
• Supplier Relationship Management: Build and maintain strong relationships with key suppliers, ensuring they meet performance expectations, quality standards, and contractual agreements.
• Process, Governance & Compliance: Ensure adherence to Okta’s SS&P policies and procedures. Help develop and implement governance to drive performance, mitigate risk, and improve operational efficiency.
• Data Analysis & Reporting: Conduct internal and external data analysis to provide clear, actionable insights. Regularly update leadership on strategy progress, savings, and market trends.

Qualifications:

Minimum Qualifications:

• Bachelor’s degree in Supply Chain Management, Business, Finance, or a related field.
• 3-5 years of Strategic Sourcing experience within indirect/services categories and overall procurement experience.
• Proven ability to lead contract and commercial term negotiations.
• Independently run and manage RFPs.
• Experience managing multiple projects in a fast-paced, dynamic environment.
• Strong analytical, problem-solving, and project management skills.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• Familiarity with the procure-to-pay process and proficiency in tools like Google Workspace and MS Office Suite (Excel, PowerPoint). 

Preferred Qualifications:

• Professional certifications such as CSCP, CPSM, or CPIM.
• Strong negotiation skills and experience in leading negotiations across various services and indirect categories
• Ability to be responsible for multiple projects with tight target dates
• Familiarity with the procure-to-pay process and vendor management principles
• Excellent project management and time management skills
• Proficiency with analytics and reporting
• Experience with ERP and financial systems. Familiarity with Coupa, Workday/ScoutRFP is a plus

#LI-MK1

#LI-hybrid

P25146_3434223

Okta’s Strategic Sourcing and Procurement (SS&P) team is looking for an experienced Category Manager to support and lead sourcing activities for our Marketing spend globally. The primary objective of this position is to maximize value, minimize risk, and ensure our marketing team has the supplier support it needs to succeed.

In this role, you will be a trusted partner to our Marketing stakeholders, helping to standardize and streamline procurement processes. You will be responsible for developing and executing the sourcing strategy for the Marketing category, leading complex negotiations, and driving cost-saving initiatives while maintaining service quality.

We are looking for a proactive, organized, and collaborative individual who works well in a fast-paced environment. This role will report to the Manager, Strategic Sourcing -  Marketing. The is a  hybrid role (2 days a week in office) and must be based in either  Bellevue, WA, or the San Francisco Bay Area.

Key Responsibilities:

Qualifications:

• Bachelor’s degree in Supply Chain Management, Business, Finance, or a related field.
• Minimum of 3+ years of experience in strategic sourcing and procurement, with experience in Marketing including Creative & Brand, PR/Communications, Swag, Paid Media, Web Marketing and Events
• Proven ability to lead contract and commercial term negotiations independently.
• Experience managing multiple projects in a fast-paced, dynamic environment.
• Strong analytical, problem-solving, and project management skills.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• Familiarity with the procure-to-pay process and proficiency in tools like Google Workspace and MS Office Suite (Excel, PowerPoint). 

Preferred Qualifications:

• Professional certifications such as CSCP, CPSM, or CPIM.
• Strong negotiation skills and experience in leading negotiations across various services and indirect categories
• Independently run and manage RFPs
• Ability to be responsible for multiple projects with tight target dates
• Familiarity with the procure-to-pay process and vendor management principles
• Excellent project management and time management skills
• Proficiency with analytics and reporting
• Experience with ERP and financial systems. Familiarity with Coupa, Workday/ScoutRFP is a plus

#LI-MK1

#LI-hybrid

P-3180_3357990

The Community You Will Join:

The Relevance & Personalization (R&P) team is Airbnb's matching intelligence engine — a talented team of ML engineers, applied researchers, and technical program managers who connect guests to the right listings across every surface and help hosts compete and thrive in our marketplace. We work at the intersection of search ranking, recommendations, personalization, and generative AI, and we're building toward a future where Airbnb feels less like a search engine and more like a knowledgeable travel companion that understands your needs across your entire trip journey.

The Difference You Will Make:

As Product Manager for Relevance & Personalization, you will help set the strategy and drive execution for some of Airbnb's highest-leverage AI systems. You'll own the roadmap and shape how personalization works across the guest journey, and help define how we close the feedback loop for hosts. You'll partner with engineers, researchers, designers, and cross-functional teams to ship systems that directly drive bookings, guest satisfaction, and host success — at global scale.

A Typical Day: 

• Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences
• Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health
• Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design
• Align cross-functional partners — Guest, Host, MarTech, Trust & Safety, Customer Support — on shared goals and sequencing
• Drive the Tripcycle vision: ensuring R&P's intelligence layer connects across the full trip lifecycle, from inspiration through post-trip
• Design and oversee A/B experiments with rigorous metric design and long-term effect measurement
• Translate complex technical tradeoffs into clear decisions for engineering teams and concise narratives for leadership
• Foster an environment where engineers and product managers collaborate on building the future
• Stay close to guests and hosts: synthesize user research, marketplace data, and competitive signals to sharpen your intuition and refine strategy

Your Expertise:

• 10+ years of product management experience, with at least 3 years on ML, search, recommendations, or AI-powered products at scale
• Track record of owning strategy and roadmap for technically complex systems — not just managing features, but setting direction and making hard prioritization calls
• Strong experimentation fluency: comfortable designing A/B tests, interpreting counterfactual results, and reasoning about proxy metrics vs. long-term outcomes
• Experience working on two-sided marketplaces or platforms where you balanced supply-side and demand-side tradeoffs
• Ability to earn the respect of Staff and Principal-level engineers and researchers — you don't need to write code, but you need to engage at a level that builds credibility
• Clear, structured communicator who can distill complex technical tradeoffs for executives and translate strategic intent into actionable guidance for engineers
• Experience with LLM-based products in production — ideally involving evaluation challenges, latency constraints, or safety and guardrail work (preferred)
• Familiarity with reinforcement learning, contextual bandits, or explore/exploit frameworks in a product context (preferred)
• Background working alongside applied researchers or with teams that publish externally (preferred)

Your Location:

Due to the nature of this position, the successful applicant will need to be based in San Francisco, CA to be able to conduct their work. Currently, employees can not be located in: Alaska, Indiana, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin, Alabama, Mississippi, Oklahoma, Delaware And Rhode Island. This list is continuously being updated, please check back with us if the state you live in is on the exclusion list.  If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. 

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

About this role

The Account Manager, Fulfillment owns the post-onboarding relationship for a portfolio of brands enrolled in Fulfilled by Faire. This is a commercially-oriented role sitting at the intersection of customer success, strategic account management, and operational consulting. The AM is accountable for brand retention, unlocking addressable SKUs within FbF, and driving the consolidation of non-Faire wholesale volume onto the platform — ultimately increasing FbF's share of each brand's total distribution.

This role requires equal fluency in relationship management and data-driven storytelling. The best AM will translate operational metrics into commercial conversations, coach brands on the cost, ease, and growth benefits of FbF, and proactively identify at-risk accounts before churn signals become churn events.

What you’ll do 

1. Business Reviews & Brand Relationships

• Own the QBR/MBR cadence for your portfolio of brands — prepare, deliver, and follow up on structured business reviews that connect FbF operational health to brand revenue outcomes. Note: this is specific to Fulfillment, different than BSMs
  • BSM = general portfolio of programs and brand perf on Faire, how's it all going, ROI of each program etc.
  • Fulfillment AM = goal of retention + revenue; then how to coach brands on cost/ease/growth
• Build multi-threaded relationships within brand accounts (founder, ops lead, sales director) to ensure Faire has a durable presence beyond a single point of contact.
• Develop and maintain a living account plan for each brand documenting their wholesale strategy, growth goals, pain points, and consolidation opportunity.
• Track and surface brand health signals (fulfillment SLA trends, return rates, catalog coverage, order velocity) to shape the review narrative and prioritize interventions.

2. Churn Prevention & Retention

• Maintain a real-time risk register for your portfolio — flag brands showing signs of disengagement (declining order volume, SLA friction, support ticket escalation, low catalog activity) and activate retention protocols before churn is formally triggered.
• Lead escalation management for brands experiencing fulfillment issues; coordinate internally with FbF Ops and Warehouse teams to resolve and close the loop with the brand (including post onboarding questions + feedback)
• Build and recommend custom “save” plans for at-risk accounts, including fee concessions, operational audits, and executive engagement where warranted (ie where to offer appeasements and program benefits)
• Conduct structured off-boarding interviews with any brand that churns to capture root cause and feed insights back to product, ops, and leadership.

3. Consolidation & Non-Faire Wholesale Volume

• Map each brand's total wholesale footprint — identify the volume, channels, and retail segments currently fulfilled outside of Faire and quantify the consolidation opportunity.
• Build and present a compelling consolidation case tailored to each brand: cost per order comparison (FbF vs. 3PL vs. self-fulfill), SLA reliability benchmarks, and projected net margin impact of migrating volume to FbF.
• Develop milestone-based migration plans for brands willing to consolidate, coordinating with Warehouse Ops to ensure capacity and onboarding support.
• Track consolidation pipeline and report GMV-at-risk (volume outside Faire) alongside GMV-converted (volume successfully moved to FbF) in your portfolio metrics.

4. Catalog Penetration & Upsell

• Audit each brand's active Faire catalog against their full SKU assortment — identify categories, price points, or product lines with low representation on the platform.
• Partner with brands to expand catalog depth and breadth, with particular focus on high-velocity SKUs and seasonal assortment that can drive incremental retailer demand.
• Position catalog growth as a retention lever: more SKUs in FbF increases platform stickiness and makes brand consolidation structurally harder to reverse

Qualifications

• 3–5 years of experience in account management, customer success, or strategic partnerships — preferably in a marketplace, logistics, e-commerce, or B2B SaaS context.
• Demonstrated track record of owning commercial outcomes (retention, expansion revenue, or upsell) within a named account portfolio.
• Strong analytical fluency — able to pull and synthesize data from BI tools (Looker, Mode, Snowflake) to build business cases and executive-level narratives.
• Excellent written and verbal communication; comfortable presenting to brand founders and operators with conviction and clarity.
• Experience managing escalations and cross-functional coordination under time pressure.

Preferred

• Background in wholesale, retail supply chain, 3PL operations, or fulfillment — understanding of landed cost economics and operational trade-offs is a meaningful differentiator.
• Experience at a marketplace or platform company with both buyer and seller stakeholders.
• Familiarity with Zendesk, Salesforce, or similar CRM/support tooling.
• Comfort with ambiguity and iterative process-building; this role will help define its own playbook.

Salary Range

On-Target Earnings (OTE) Range
San Francisco: the pay range for this role is $132,000 to $181,500 per year.

This role will also be eligible for equity and benefits. Actual On-Target Earnings (OTE) will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The OTE range provided is subject to change and may be modified in the future.

About the role

We are looking for a Product Security Manager to lead a team focused on cloud, data, and AI security within our Product Security organization.

This role is responsible for securing our cloud infrastructure, protecting sensitive data, and enabling safe adoption of AI across our products and internal systems. You will work closely with engineering, product, and data teams to ensure that modern systems, including AI-powered features, are designed and operated securely.

While cloud and data security are core pillars, AI security is an increasingly critical area of focus. You will help define how we safely leverage AI technologies while managing risks such as data exposure, misuse, and insecure integrations.

This role operates within a flexible POD model, requiring you and your team to move fluidly across security domains based on business priorities.

The base salary offered for this role and level of experience will begin at $152,000 and up to $210,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to 

• Own the security posture of cloud infrastructure, data systems, and AI-enabled applications across product surfaces
• Influence data, ML, and infrastructure team roadmaps and drive alignment on security priorities without direct authority
• Partner with engineering and product teams to embed security into system design and development workflows
• Lead and grow a team of security engineers, setting a high bar for technical execution, ownership, and impact
• Define and execute strategy for securing cloud-native architectures and sensitive data at scale
• Establish guardrails and secure design patterns for AI adoption, including safe integration of third-party and internal AI systems
• Identify and mitigate risks related to AI systems, including prompt injection, data leakage, and misuse of models or APIs
• Build scalable controls and automation around identity, access, encryption, and data protection
• Operate effectively within a POD model, shifting focus across security domains based on business needs
• Lead and support response efforts for security incidents related to cloud, data, and AI risks

To begin in this role, you have

• 5+ years of experience in security engineering, with significant experience in cloud and/or data security
• 2+ years of experience managing or leading security engineers
• Strong understanding of cloud platforms (AWS, GCP), Infrastructure as Code (IaC), and modern infrastructure patterns
• Experience designing or securing systems that handle sensitive or regulated data
• Experience securing or evaluating AI/ML systems, or demonstrated ability to operate effectively in ambiguous and emerging security domains
• Strong technical judgment and the ability to go deep in architecture and security discussions when needed
• Experience operating in fast-paced, product-driven environments with shifting priorities
• Strong communication skills with the ability to translate security risks into business impact

#LI-JL1 #LI-Onsite

About the Role

The Deposit & Insights team is looking for a skilled backend engineer to join our team. You'll be leveraging deeply individualized spending insights and member spending behavior to give our members access to the best tools that enable them to spend safely. This role involves collaborating cross functionally, experimenting quickly, and iterating on solutions to find the best points of conversion.

The base salary offered for this role and level of experience will begin at $133,000 and up to $184,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Drive technical design and architectural decisions, while mentoring engineers and fostering cross-functional collaboration
• Lead and contribute to multiple projects simultaneously, balancing ownership of key initiatives with support across broader team efforts
• Build and maintain robust, low-latency APIs and backend services that power our Trust and Safety platforms
• Become the domain expert in our platform architecture, providing technical decisions and solutions to refine our maturing platforms
• Partner with data engineers, analysts, and product managers to ship impactful features that enhance member protection and experience
• Improve platform reliability and performance through thoughtful system architecture, observability practices, and automation
• Evolve our experimentation, policy lifecycle, and ML integration capabilities to support smarter and faster decision-making at scale
• Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary.

To thrive in this role, you have

• 3+ years of experience developing software in a production environment at scale
• Prior experience serving as a technical lead for a team and on complex projects—driving architectural decisions, coordinating execution, and aligning cross-functional teams
• Proven experience with Ruby on Rails or comparable frameworks
• Experience with transactional databases and caching systems
• Deep understanding of architectural patterns for large-scale web applications
• Commitment to mentoring engineers and fostering team development
• An appreciation of maintainable and well-tested code
• Curiosity and passion for diving deeply into system architectures and technical challenges
• Experience in fast-paced or early-stage environments is a strong plus

#LI-Onsite #LI-AA1

About the role 

We are hiring a Compliance Fair Lending Lead to join our Business Advisory team to support the exciting products and services at Chime, with a focus on fair lending and fairness. As a Fair Lending Lead, you will support new and existing Chime product development by advising product, marketing, credit risk, and DS/ML teams on compliance and strategies for fair lending and fairness compliance. You’ll also provide advisory support for our Instant Loans product. You will monitor the evolving regulatory landscape and advise on enhancements to existing Chime products, services, and models to remain fair and responsible as they continue to scale.  

The base salary offered for this role and level of experience will begin at $127,000.00 and up to $175,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to 

• Support the maintenance, enhancement, and execution of the fair lending compliance program, including governance, policies and procedures, advisory frameworks, risk assessment, and testing
• Perform ongoing reviews of consumer complaints, marketing & advertising, loan documentation, and all applicable consumer-related forms for fair lending and fairness risks
• Evaluate proposed business change to ensure compliance with applicable fair lending-related laws and regulations
• Drive corrective actions taken to address fair lending issues, including assisting with the implementation of remediation, conducting follow-up reviews to determine the adequacy, and effectiveness of the action taken
• Establish and maintain strong relationships with internal and external stakeholders.

To thrive in this role, you have

• 7+ or more years of experience in banking, credit, lending, or equivalent experience in product compliance, with at least 4+ years working in ECOA and UDAAP compliance. Fintech experience is a plus.
• Demonstrated knowledge of key regulations including but not limited to ECOA, UDAAP and other consumer protection regulations
• Experience in advising product, marketing, machine learning teams on issues related to ECOA and UDAAP compliance. 
• Excellent analytical, verbal and written communication skills.
• Experience independently executing quality, timely compliance management system components. 
• Ability to develop solutions and advise on  issues, with minimal oversight from your leadership team.
• A desire to collaborate and have the ability to influence both your colleagues and external partners to achieve consensus on regulatory risk issues and appropriate mitigation. 
• Experience working with statistics, analytics, and other technical tools is a plus.

#LI-Hybrid #LI-BE1

About the Role

The Turbo team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale.

Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design.

You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal.

Requirements

We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay.

You might be a good fit if you:

• Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others:
• Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving.
• RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models.
• Model architecture design for Transformers or other large neural nets.
• Distributed systems / high‑performance computing for ML.
• Are comfortable working from algorithms to engines:
• Strong coding ability in Python
• Experience profiling and optimizing performance across GPU, networking, and memory layers.
• Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack.
• Have a solid research foundation in your area(s) of depth:
• Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems).
• Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API).
• Operate well as a full‑stack problem solver:
• You naturally ask: “Where in the stack is this really bottlenecked?”
• You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins.

Minimum qualifications

• 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source).
• Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience.
• Demonstrated experience owning complex technical projects end‑to‑end.

If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement.

Responsibilities

• Advance inference efficiency end‑to‑end
• Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference.
• Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc.
• Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost.
• Unify inference with RL / post‑training
• Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems.
• Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper.
• Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack.
• Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers.
• Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design.
• Own critical systems at production scale
• Profile, debug, and optimize inference and post‑training services under real production workloads.
• Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed.
• Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously.
• Provide technical leadership (Staff level)
• Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training.
• Mentor other engineers and researchers on full‑stack ML systems work and performance engineering.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the role

As a Customer Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment.

Responsibilities

• Engage directly with customers to tackle and resolve complex technical challenges involving our cutting-edge Kubernetes GPU clusters; ensure swift and effective solutions every time.
• Become a product expert in our GPU Cluster service, serving as the last line of technical defense before issues are escalated to Engineering and Product teams.
• Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction.
• Transform customer insights into action by identifying patterns in support cases and working with Engineering and Go-To-Market teams to drive Together’s roadmap (e.g., future models to support)
• Maintain detailed documentation of system configurations, procedures, troubleshooting guides, and FAQs to facilitate knowledge sharing with team and customers.
• Be flexible in providing support coverage during holidays, nights and weekends as required by business needs to ensure consistent and reliable service for our customers.

Requirements

• 3+ years of experience in a customer-facing technical role with at least 1 year in a support function in AI or supporting a mission-critical API in SaaS
• Strong technical background, with knowledge of AI, ML, GPU technologies and their integration into high-performance computing (HPC) environments.
• Familiarity with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible) high-performance network fabrics, NFS-based storage management, container infrastructure, and scripting and programming languages.
• Foundational understanding in the installation, configuration, administration, troubleshooting, and securing of compute clusters.
• Complex technical problem solving and troubleshooting, with a proactive approach to issue resolution
• Ability to work cross-functionally with teams such as Sales, Engineering, Support, Product and Research to drive customer success.
• Strong sense of ownership and willingness to learn new skills to ensure both team and customer success.
• Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Ability to operate in dynamic environments, adept at managing multiple projects, and comfortable with frequent context switching and prioritization.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000-230,000K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

Together AI is building the AI Inference & Model Shaping Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant server-less workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and reasoning models at scale.

We are looking for an exceptional Engineering Lead to partner closely with our cross-functional engineering, infrastructure, research, and sales teams to ensure excellence of our ML API offerings. Your primary focus will be on delivering world-class inference and fine-tuning in our public APIs and customer deployments by building automation and operations processes.

This role is ideal for a highly motivated and technically adept individual who excels in fast-paced, dynamic environments. You will be in charge of designing and scaling our ML processes & tooling at production scale – optimizing operations to ensure availability and reliability for our services, across differing tenants and user loads, and in a multi-cluster deployment. You will serve as a passionate advocate for internal and external customers, providing feedback to the wider engineering and infrastructure teams to improve our systems and core business metrics. If you thrive in a collaborative, problem-solving environment and are driven to deliver operational excellence, we encourage you to apply for this exciting opportunity.

Key Responsibilities

• Own availability and performance SLAs for production inference and fine-tuning services across serverless and dedicated deployments
• Own & improve testing, deployment, configuration management, and monitoring practices for multi-cluster ML infrastructure – partnering closely with Infra SREs
• Build self-serve tooling and automation to reduce operational toil and enable self-serve offerings.
• Define and enforce configuration best practices for inference engines (SGLang, TRT-LLM, vLLM etc.) to prevent runtime issues
• Lead incident response, conduct postmortems, and drive reliability improvements
• Mentor team members and potentially grow into hiring/team building as the organization scales
• Partner with infrastructure and ML engineering teams to improve system reliability and cost efficiency

Required Qualifications

• 5+ years operating production ML inference or training systems at scale
• 2+ years in senior IC or tech lead roles, with demonstrated mentorship and technical leadership experience. Having built or scaled teams is a plus.
• Deep expertise with Kubernetes, multi-cluster orchestration, and ML serving frameworks
• Experience with multi-tenant SaaS platforms
• Proven track record of SLA ownership with specific metrics (99.9% uptime, p99 latency targets)
• Customer escalation and incident communication experience
• Experience with LLM inference serving systems (SGLang, vLLM, TRT-LLM, or similar)
• Ability to influence cross-functional teams and make deployment/architecture decisions

Nice to Have

• Experience building internal developer platforms or self-serve tooling
• Background in cost optimization for GPU infrastructure
• Contributions to open-source ML infrastructure projects

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $250,000 - $300,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

This is the first dedicated data hire on Together AI's Finance team. You will own the data layer that Finance runs on — building from scratch the models, pipelines, and reporting infrastructure that allow Strategic Finance, FP&A, and Accounting teams to get reliable answers quickly. The person in this role will have direct exposure to every part of the Finance organization and a real opportunity to shape how data-driven decision-making develops here as the company scales.

A significant portion of your work will touch the data behind the economics of Together's infrastructure, which sits behind nearly every financial question we ask. You will work closely with Together's Data and Commerce engineering team, which owns the underlying billing pipelines and data warehouse. Your job is to define and build the modeling and reporting layer that turns raw operational data into finance-grade datasets — aligning on data contracts, representing Finance's requirements in data design decisions, and ensuring the metrics Finance depends on are correct, documented, and trusted.

Responsibilities

• Own and evolve the dbt transformation layer for Finance: design, build, test, document, and maintain models covering billing, financial performance, compute unit economics, and operational metrics
• Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate Finance dbt runs, data quality checks, and downstream dependencies reliably
• Deliver dashboards and reporting in Hex for the executive team covering financial performance, utilization, and key operating metrics
• Partner with Strategic Finance, FP&A, and Accounting teams on the data infrastructure behind forecasting, cost modeling, and other financial analyses
• Set data quality standards across Finance data products and own incident response when Finance-critical pipelines break
• Build the data foundation – clean, well-structured, documented, and reliably maintained – that enables Finance team to self-serve data analysis and supports AI automation and agentic workflows 

Requirements

• 5+ years in an analytics engineering or data engineering role, with meaningful time supporting Finance or business operations teams
• Expert SQL and production-grade dbt experience — models, tests, docs, snapshots, incremental strategies; you've designed a dbt project from scratch and maintained it
• Hands-on experience with Snowflake and Airflow in production; familiarity with Astronomer and the Cosmos dbt integration is a strong plus
• Solid dimensional modeling fundamentals: star schemas, slowly changing dimensions, fact table grain — you can apply Kimball principles without needing to look them up
• Strong dashboarding skills with a track record of executive-facing reporting that people actually use; experience with Hex or a comparable notebook/BI tool
• Clear communicator who can align stakeholders on metric definitions and translate between engineering tradeoffs and Finance requirements in both directions
• High comfort with ambiguity; this role will require scoping problems from scratch, not executing against pre-defined specs

Nice to Have

• Experience with financial data or billing data such as ARR, usage-based billing, invoice reconciliation, revenue recognition patterns, etc.. We operate a usage-based billing system and this context transfers directly.
• Experience with PII handling, data masking, access-tier modeling, or compliance work (SOC 2, ISO 27001, GDPR, CCPA).
• Familiarity with lakehouse patterns (Iceberg, Delta, Hudi) and hybrid warehouse/lake architectures.
• Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.
• Experience with Hex, Metabase, or similar notebook/BI tooling that sits on top of your dbt models.
• Prior experience in a high-growth AI/ML infrastructure or platform company

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200k -$240k + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy.  

About the Role

Together AI is looking for an ML Engineer who will develop systems and APIs that enable our customers to perform inference and fine tune LLMs. Relevant experience includes implementing runtime systems that perform inference at scale using AI/ML models from simple models up to the largest LLMs.

Requirements

• 5+ years experience writing high-performance, well-tested, production quality code
• Bachelor’s degree in computer science or equivalent industry experience
• Familiar with LLM inference ecosystem, including frameworks and engines (e.g. vLLM, SGLang, TRT, ...)
• Demonstrated experience in building large scale, fault tolerant, distributed systems like storage, search, and computation
• Expert level programmer in one or more of Python, Go, Rust, or C/C++
• Experience implementing runtime inference services at scale or similar

Responsibilities

• Design and build the production systems that power the Together Cloud inference and fine-tuning APIs, enabling reliability and performance at scale
• Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world
• Analyze and improve efficiency, scalability, and stability of various system resources
• Conduct design and code reviews
• Create services, tools & developer documentation
• Create testing frameworks for robustness and fault-tolerance
• Participate in an on-call rotation to respond to critical incidents as needed

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $220,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI!

Responsibilities

• Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale.
• Develop and optimize runtime inference services for large-scale AI applications.
• Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
• Conduct design and code reviews to ensure high standards of quality.
• Create services, tools, and developer documentation to support the inference engine.
• Implement robust and fault-tolerant systems for data ingestion and processing.

Requirements

• 3+ years of experience writing high-performance, well-tested, production-quality code.
• Proficiency with Python and PyTorch.
• Demonstrated experience in building high performance libraries and tooling.
• Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale.
• Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum
• Preferred: Knowledge of AI inference techniques such as speculative decoding.
• Preferred: Knowledge of CUDA/Triton programming.
• Nice to have: Knowledge of Rust, Cython and compilers.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society. Together, we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI. Our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey to build the next-generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other competitive benefits. The US base salary range for this full-time position is $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level, and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunities to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

About the Role

Our team focuses on enabling custom models and dedicated inference on Together. We are responsible for building a container platform, optimizing autoscaling, minimizing cold starts, achieving the best end-to-end model performance, and providing a best-in-class developer experience with great tooling. We often focus on video or audio generation across the stack: CUDA kernels, pytorch optimization, inference engines, container orchestration, queueing theory, etc. An ideal candidate will be great at profiling/optimization but know the word kubernetes, or be intimately familiar with multi-cluster scheduling and have some sense of ML bottlenecks.

Responsibilities

• New hires may work on multi-cluster orchestration, portfolio optimization, predictive autoscaling, control panes, model bring-up, model optimization, APIs for managing deployments, inference worker SDKs, and CLI tools.
• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable software and IaC for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems.
• Experience running serverless inference platforms, doing model bring-up on short notice, being on call, or running a cloud provider is a very big plus
• Good taste and ability to thoughtfully discuss how what you’ve built has failed over time
• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
• Excellent understanding of low level operating systems concepts including concurrency, networking and storage, performance and scale
• Expert-level programmer in one or more of Python, Golang, Rust, C++, or Haskell
• Proficiency in writing and maintaining Infrastructure as Code (IaC) using tools like Terraform
• Experience with Kubernetes internals or other container orchestration systems
• Sound judgement for when to use and when to not use LLMs for code
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
• Writing-heavy roles or companies are a plus

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

This is a research engineering role with direct production impact. You won’t be publishing ideas in isolation—you will translate new RL algorithms, scheduling methods, and inference optimizations into production-grade systems that power Together’s API. Success in this role means shipping measurable improvements in latency, throughput, cost, and model quality at scale. We are looking for researchers who enjoy owning systems end-to-end and turning frontier ideas into robust infrastructure.

The Core ML (Turbo) at Together AI team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale.

Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design.

You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal.

Responsibilities

• Advance inference efficiency end‑to‑end
• Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference.
• Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc.
• Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost.
• Unify inference with RL / post‑training
• Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems.
• Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper.
• Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack.
• Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers.
• Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design.
• Own critical systems at production scale
• Profile, debug, and optimize inference and post-training services under real production workloads, taking research ideas all the way to stable, measurable improvements in deployed systems.
• Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed.
• Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously.
• Provide technical leadership (Staff level)
• Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training.
• Mentor other engineers and researchers on full‑stack ML systems work and performance engineering.

Requirements

We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay.

You might be a good fit if you:

• Have a bias toward implementation and shipping—you are excited to modify real engines and services, not just prototype in research code.
• Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others:
• Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving.
• RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models.
• Model architecture design for Transformers or other large neural nets.
• Distributed systems / high‑performance computing for ML.
• Are comfortable working from algorithms to engines:
• Strong coding ability in Python
• Experience profiling and optimizing performance across GPU, networking, and memory layers.
• Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack.
• Have a solid research foundation in your area(s) of depth:
• Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems).
• Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API).
• Operate well as a full‑stack problem solver:
• You naturally ask: “Where in the stack is this really bottlenecked?”
• You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins.

Minimum qualifications

• 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source).
• Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience.
• Demonstrated experience owning complex technical projects end‑to‑end.

If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

Together AI is building the Inference Platform that powers the world's most advanced generative AI models. Your role will be a critical bridge between cutting-edge research and real-world applications, focusing on making translating our internal model training research to production-ready deployment for our customers. This involves a deep commitment to data-centric development, meticulous hyperparameter tuning, and rigorous checkpoint evaluation before models ever hit production.

This role will involve understanding customer specific needs and fine-tuning models on our internal data recipe and their proprietary data. The goal is to transform general-purpose models into highly performant, specialized tools that solve real business problems. You will not be training foundation models from scratch but rather focusing on creating highly efficient, specialized models by working with dedicated GPU clusters.

Responsibilities

• Design and iterate on novel speculator algorithms, combining architectural innovations with carefully curated data to push the frontier of accuracy–efficiency tradeoffs.
• Be the critical link between raw data and a production-ready model, seeing your work directly impact our customers' success.
• Work in a fast-paced, high-impact role at the cutting edge of generative AI.
• Collaborate with a team of experts dedicated to solving real-world, high-performance challenges.
• You'll collaborate directly with customers to understand their needs, and work closely with our core inference and Applied ML research teams to integrate your work into the production platform.
• A culture of deep technical ownership where you are empowered to take on and solve challenging problems

Requirements

• A genuine love for data curation and processing, with a meticulous attention to detail. You believe that great models start with great data.
• Demonstrated ability to perform effective hyperparameter searches and understand the trade-offs involved in tuning models for specific tasks.
• Experience working with and building on top of existing training codebases. You are comfortable navigating complex code and contributing to its improvement.
• Strong attention-to-detail in evaluating model checkpoints to ensure they meet strict quality, performance, and reliability standards.
• Experience with Python and PyTorch.
• Familiarity with SLURM and/or Kubernetes clusters and experience submitting and managing jobs in a high-performance computing environment.
• Familiarity with modern LLMs and generative models.
• Basic understanding of distributed training frameworks (e.g., FSDP, DeepSpeed).
• Bachelor’s, Master’s degree, or Ph.D. in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, ATLAS, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale.

If you get a thrill from optimizing latency down to the last millisecond, this is your playground. You’ll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory.

You’ll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency.

• Shape the core inference backbone that powers Together AI’s frontier models.
• Solve performance-critical challenges in global request routing, load balancing, and large-scale resource allocation.
• Work with state-of-the-art accelerators (H100s, H200s, GB200s) at global scale.
• Partner with world-class researchers to bring new model architectures into production.
• Collaborate with and contribute to the open source community, shaping the tools that advance the industry.
• A culture of deep technical ownership and high impact — where your work makes models faster, cheaper, and more accessible.
• Competitive compensation, equity, and benefits.

Responsibilities 

• Build and optimize global and local request routing, ensuring low-latency load balancing across data centers and model engine pods.
• Develop auto-scaling systems to dynamically allocate resources and meet strict SLOs across dozens of data centers.
• Design systems for multi-tenant traffic shaping, tuning both resource allocation and request handling — including smart rate limiting and regulation — to ensure fairness and consistent experience across all users.
• Engineer trade-offs between latency and throughput to serve diverse workloads efficiently.
• Optimize prefix caching to reduce model compute and speed up responses.
• Collaborate with ML researchers to bring new model architectures into production at scale.
• Continuously profile and analyze system-level performance to identify bottlenecks and implement optimizations.

Requirements

• 5+ years of demonstrated experience building large-scale, fault-tolerant, distributed systems and API microservices.
• Strong background in designing, analyzing, and improving efficiency, scalability, and stability of complex systems.
• Excellent understanding of low-level OS concepts: multi-threading, memory management, networking, and storage performance.
• Expert-level programming in one or more of: Rust, Go, Python, or TypeScript.
• Knowledge of modern LLMs and generative models and how they are served in production is a plus.
• Experience working with the open source ecosystem around inference is highly valuable; familiarity with SGLang, vLLM, or NVIDIA Dynamo will be especially handy.
• Experience with Kubernetes or container orchestration is a strong plus.
• Familiarity with GPU software stacks (CUDA, Triton, NCCL) and HPC technologies (InfiniBand, NVLink, MPI) is a plus.
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.

We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.

This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.

• Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.
• Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.
• Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.
• Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.
• Join a small, early-stage team with outsized impact on a fast-growing product area.

Responsibilities

• Optimize inference performance for voice models (STT, TTS, speech-to-speech) — targeting best-in-class TTFB, throughput, and GPU utilization across our curated model set.
• Productionize voice models on serverless and dedicated endpoints, including batching strategies, streaming inference, and memory management tailored to audio workloads.
• Build and maintain a voice model evaluation framework — measuring WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation accuracy for TTS.
• Enable new model architectures in our serving stack as the field evolves, including audio-native LLMs, codec-based models (SNAC), and speech-to-speech systems.
• Collaborate with model partners to integrate and optimize their models (Cartesia, Deepgram, Rime, and others) running on Together's infrastructure.
• Profile and debug performance across the full inference stack — from GPU kernels to framework-level bottlenecks — and ship measurable improvements.
• Work with the platform engineering side of the team to ensure the serving layer meets the latency and reliability requirements of real-time voice APIs.
• Contribute to voice model fine-tuning capabilities (STT and TTS) as we enable customers to build differentiated voice experiences on Together.
• Lay the groundwork for multiple new products down the line.

Requirements

• 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure.
• Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs.
• Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging).
• Track record of shipping ML systems to production with measurable performance improvements.
• Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting.
• Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.
• Experience with speech and audio ML (ASR, TTS architectures, audio signal processing) is a strong plus but not required — you can learn this quickly if you have strong ML engineering fundamentals.
• Familiarity with audio codecs and tokenization schemes (SNAC, Encodec, DAC) is a plus.
• Experience training or fine-tuning speech models is a plus.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $260,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.

We're looking for a Senior Platform Engineer to own the API and infrastructure layer for voice workloads. You'll build the real-time WebSocket and HTTP APIs that developers use to ship voice experiences, design autoscaling for latency-sensitive streaming workloads, and ensure our multi-provider voice platform is reliable enough for production voice agents handling millions of calls.

This is a foundational hire on a small, high-impact team. Voice APIs have fundamentally different infrastructure requirements than text-based inference — bidirectional audio streaming, stateful connections, tight latency SLOs, and complex multi-model routing. You'll define how developers interact with Together's voice platform as we grow from early customers to the default infrastructure for voice AI.

• Own the real-time API layer (WebSocket + HTTP streaming) that powers Together's voice platform.
• Design autoscaling and orchestration for voice workloads running on tens of thousands of GPUs.
• Build the developer experience — APIs, observability, and tooling — for a fast-growing product area.
• Work with production voice customers (contact centers, AI agents, communication platforms) to ship what they actually need.
• Join a small, early-stage team with outsized impact on a new product line.

Responsibilities

• Build and harden real-time WebSocket and HTTP streaming APIs for STT and TTS — including connection lifecycle management, backpressure, error handling, and reconnection, at the reliability bar needed for production voice agents.
• Design and ship autoscaling for voice model endpoints that handles bursty, real-time traffic patterns — accounting for concurrent connection limits, streaming state, and hard latency ceilings.
• Implement voice-specific API features: word-level alignment, speaker diarization in realtime, audio format flexibility (g711/mulaw for telephony, PCM, WebRTC formats), pronunciation controls, and multi-context WebSocket support.
• Build voice-specific observability — latency breakdowns, audio quality signals, and dashboards that help both the team and customers debug issues.
• Own multi-model normalization across our model partners (Cartesia, Deepgram, Rime, and others), ensuring consistent API behavior regardless of the underlying provider.
• Collaborate with the ML engineering side of the team on the interface between the API layer and the model serving stack, ensuring latency and reliability requirements are met end-to-end.
• Contribute to developer experience — API design, documentation, integration cookbooks, playground and showcasing how best-in-class voice agents are built.
• Lay the groundwork for multiple new products down the line.

Requirements

• 5+ years of experience building large-scale, real-time distributed systems and API services.
• Deep expertise in real-time streaming infrastructure — WebSocket server architecture, Server-Sent Events, bidirectional streaming, connection multiplexing, and stateful protocol design.
• Expert-level programming in TypeScript and Python; experience with Rust is a plus.
• Strong distributed systems fundamentals: load balancing, autoscaling, rate limiting, and traffic shaping for latency-sensitive workloads.
• Experience with Kubernetes — including custom autoscalers, resource management, and health checking for stateful services.
• Strong product sense — you care about API ergonomics and think about what developers building voice apps actually need.
• Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.
• Experience with audio or media protocols (WebRTC, g711, PCM encoding) is a strong plus.
• Familiarity with ML model serving infrastructure and how inference engines work is a plus — you'll interface with the serving layer regularly.
• Full-stack experience (React, Next.js) is a nice-to-have for contributing to developer-facing tooling.
• Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $260,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

As a Senior AI Infrastructure Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal SaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world.

Responsibilities

• Design, build, and maintain performant, secure, and highly-available backend services/operators that run in our data centers and automate hardware management, such as Infiniband partitioning, in-DC parallel storage provisioning, and VM provisioning.
• Design and build out the IaaS software layer for a new GB200 data center with thousands of GPUs.
• Work on a global multi-exabyte high-performance object store, serving massive datasets for pretraining.
• Build advanced observability stacks for our customers with automated node lifecycle management for fault-tolerant distributed pretraining.
• Perform architecture and research work for decentralized AI workloads
• Work on the core, open-source Together AI platform
• Create services, tools, and developer documentation
• Create testing frameworks for robustness and fault-tolerance

To be successful, you’ll need to be deeply technical and possess excellent communication, collaboration, and diplomacy skills. You have strong fundamental software development skills. In addition, you have strong systems knowledge and troubleshooting abilities. 

Requirements

• 5+ years of professional software development experience and proficiency in at least one backend programming language (Golang desired)
• 5+ years experience writing high-performance, well-tested, production quality code
• Demonstrated experience with building and operating high-performance and/or globally distributed micro-service architectures across one or more cloud providers (AWS, Azure, GCP)
• Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
• Deep experience with Kubernetes internals a big plus, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches thereon or Kubernetes itself
• Deep experience with VMs/hypervisors a big plus, such as QEMU/KVM, cloud-hypervisor, VFIO, virtio, PCIE passthrough, Kubevirt, SR-IOV
• Deep experience with DC networking tech + solutions a big plus, such as VLAN, VXLAN, VPN, VPC, OVS/OVN
• Experience with Cluster API or similar a big plus
• Experience working on high-performance compute, networking, and/or storage a big plus
• Experience virtualizing GPUs and/or Infiniband a big plus
• Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
• Experience with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (GitHub Actions, ArgoCD)
• Experience building IaaS or PaaS systems at scale a plus
• Experience with DPUs/SmartNICs a plus
• GPU programming, NCCL, CUDA knowledge a plus 

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

As a Senior Backend Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal StaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world.

Some of what you’ll work on:

• Work on a distributed GPU scheduling system for the on-demand clusters product, Instant Clusters.
• Build out a global management plane for managing our data center compute, networking, and storage.
• Design and build new customer-facing cloud platform services, delivering killer enterprise AI cloud features.

Responsibilities

• Identify, design, and develop foundational backend services that power Together’s cloud platform
• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable software and IaC for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
• Participate in an on-call rotation to address critical incidents when necessary

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices
• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
• Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
• Demonstrated experience with building and operating high-performance and/or globally distributed microservice architectures across one or more cloud providers (AWS, Azure, GCP)
• Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
• Experience developing against and managing a relational database, such as PostgreSQL
• Expert-level programmer in one or more of programming language (Golang preferred)
• Proficiency in version control practices and integrating IaC with CI/CD pipelines.
• Experience with Kubernetes and containers preferred
• Experience building and operating data infrastructure (Kinesis, Airflow, Kafka, etc) a plus
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

As a Solutions Architect at Together AI, you will work with customers and prospects to create business value through Generative AI applications. Solutions Architects at Together are trusted advisors to our customers that evaluate, identify and demonstrate how Together can solve their AI needs. As key contributors to our sales organization, Solution Engineers add tremendous value to the customer journey and directly impact company growth and revenue. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment.

Responsibilities

• Act as a technical advisor to our most strategic customers, deeply embedding with them to support the ideation and development of innovative applications using OSS models on Together AI
• Run complex demonstrations and POCs of Together’s entire stack, including both hardware and software solutions
• Collaborate with sales to qualify new prospects and support existing customers along their journey to build cutting-edge Generative AI solutions
• Build and maintain strong relationships with customer leadership and stakeholders, ensuring the successful deployment and scaling of their applications
• Deliver high-value feedback to our Product, Engineering, and Research teams, ensuring our platform continues to evolve to meet customer needs
• Build educational content and tooling for both internal and external use around Together’s solutions (i.e., playbooks, blogs, demos, etc.)

Qualifications

• 5+ years of experience in a customer-facing technical role with at least 2 years in a pre-sales function 
• Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Ability to consult with new and existing customers to map business needs to technical solutions
• Strong technical background, with knowledge of AI, ML, GPU technologies and their integration into high-performance computing (HPC) environments.
• Strong understanding of training, fine-tuning and inference in the context of open source LLMs
• Proficiency in Python and JavaScript, with experience building and delivering prototypes on API platforms.
• Familiarity with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible), container infrastructure Docker), and scripting and programming languages (Python, Javascript)
• Strong sense of ownership and willingness to learn new skills to ensure both team and customer success.
• Ability to operate in dynamic environments, adept at managing multiple projects, and comfortable with frequent context switching and prioritization.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US salary range for this full-time position is: $180-260K OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

About the Role

As the Partnerships Manager for our Model Ecosystem, you will be the primary architect of Together AI’s model library. This is a high-impact, cross-functional role focused on bringing the world’s leading proprietary and open-source models onto the Together platform. You will navigate an ever-evolving landscape to negotiate non-standard, creative deals that provide developers with the best possible building blocks for AI applications.

You are a "deal-maker" who thrives in ambiguity. You will sit at the intersection of Product, Finance, and Marketing, ensuring that our model roadmap is not only technically superior but commercially viable and market-facing.

Responsibilities

• Negotiate & Manage Partnerships: Lead end-to-end deal cycles with model builders across all modalities (text, image, video, etc.). You will handle everything from initial outreach to negotiating complex, creative commercial terms for both proprietary and open-source models.
• Curate the Model Library: Act as the internal champion for our "Model Library," identifying which frontier and specialized models we should bring to Together AI to maintain our competitive edge.
• Product & Engineering Alignment: Work closely with the Product team to define "bring-up" requirements and ensure new models are integrated seamlessly into our inference and fine-tuning stacks.
• Commercial Strategy: Partner with Finance to construct deal structures that balance aggressive growth with sustainable unit economics, often involving non-standard incentive structures.
• Go-to-Market & Co-Selling: Collaborate with Partner Marketing to announce new integrations and create momentum. You will also engage in co-selling efforts, helping our Sales team understand how to leverage specific partner models to win enterprise deals.

Requirements

• Creative Deal Maker: You have a track record of constructing partnership agreements that don’t follow a standard template. You can navigate complex IP, revenue-share, and exclusivity discussions with ease.
• High EQ & Collaborative: You are partner-oriented. You know how to build trust quickly and find the "win-win" in a competitive environment.
• Technical Curiosity: While you don’t need to be an ML researcher, you should have the technical depth to discuss model architecture, context windows, and inference requirements with product teams.
• Relevant Experience: 5-7+ years in Business Development or Strategic Partnerships. We value experience from high-growth API, cloud infrastructure, or developer platform companies (think Stripe, MongoDB, or Twilio) where you managed complex ecosystems.
• AI-Native Mindset: You work at pace with a relentless sense of urgency. You prefer "done and iterating" over "perfect and stagnant."

Preferred Qualifications

• Direct experience working with LLM labs or open-source AI communities.
• Experience in "co-selling" motions where partnerships directly drove revenue.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $270K - 300K OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy.  

About the Role

As a Senior Infrastructure Technical Program Manager (TPM) at Together AI, you will be at the core of building, optimizing, and scaling the global GPU resources needed for a pioneering AI infrastructure company. Your role is crucial in ensuring that the backbone of our AI models, thousands of GPUs distributed around the world, operates efficiently and reliably, enabling cutting-edge AI advancements that democratize access to AI technology globally.  You will drive cross-functional excellence by streamlining critical workflows and enhancing communication across internal and external teams. Join top engineers, researchers, and innovators to shape the future of AI infrastructure and power the next generation of AI-driven solutions.

Responsibilities

• Product Development: Design and build products for AI researchers, developers, and enterprise customers, translating technical requirements into product features and collaborating with research, engineering, and design teams. Develop and execute strategic plans for the Observability, Storage, Network Engineering, and Security infrastructure teams.
• End-to-End Product Ownership: Own a comprehensive product roadmap, detailing key features, enhancements, and releases. Drive end-to-end product development, manage development and testing, and lead launches.
• Stakeholder Engagement: Engage with stakeholders to understand their needs, pain points, and feedback. Drive initiatives to enhance customer satisfaction and loyalty through product improvements and innovative solutions.
• Cross-Functional Execution: Lead and align diverse cross-functional teams — including Research, Engineering, DevOps, SRE, and Go-to-Market — to ensure seamless project delivery and organizational success.

Requirements

• ML Product or Infrastructure Experience: 5+ years of experience building and scaling AI/ML-powered products and infrastructure, specifically collaborating with research and engineering teams.
• Proven experience with large-scale technology deployments, including cloud computing platforms, decentralized cloud infrastructure, and distributed systems (e.g., containerization and orchestration tools).
• Familiarity with the technical domains of Observability, Storage, Network Engineering, and Security for infrastructure.Experience with cloud computing platforms, decentralized cloud infrastructure, and/or similar large-scale technology deployments.
• Familiarity with cloud-based technologies (e.g., AWS, Google Cloud, or Azure)
• Technical Foundation: Bachelor's or Master's degree in Machine Learning, Computer Science, Engineering, or a related field.  
• Exceptional analytical and problem-solving skills, with a demonstrated ability to identify and proactively mitigate technical risks
• Experience using AI tools, such as ClaudeCode or similar, to accelerate analytical progress.
• Executive and Organizational Acumen
• Proven ability to thrive in a fast-paced, ambiguous startup environment, prioritizing complex tasks and managing multiple simultaneous projects.
• Strong organizational abilities to build cross-functional alignment and establish clear, focused priorities.
• A proactive and collaborative team-oriented approach, demonstrating a willingness to drive necessary outcomes across the company.
• Excellent communication and program management skills for effective collaboration with both internal stakeholders and external vendors.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $225k to 265k + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. This is a hybrid role based in the Bay Area.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

Together AI is building high-performance AI inference infrastructure and the software platform around it. We're looking for a senior Analytics Engineer who sits at the intersection of data engineering and business intelligence — someone who can turn raw, complex data into clean, trusted, well-documented models that the whole company can reason from.

You'll own the transformation layer of our data warehouse: shaping bronze/silver/gold models, designing dimensional schemas, and acting as the connective tissue between engineering systems and business stakeholders. You are equally comfortable deep in a dbt project and in a room with Finance, GTM, and Product aligning on definitions.

Requirements

• Expert SQL: window functions, complex aggregations, query optimization, cost-aware pattern selection, proficiency in Snowflake or equivalent cloud warehouse.
• dbt: deep, production-grade experience — models, tests (singular + generic), docs, snapshots, macros, packages, and incremental strategies. You've designed a dbt project from scratch and maintained it in production.
• Airflow / Astronomer: production DAG authoring, backfill handling, reliability patterns, and the Cosmos dbt integration.
• Dimensional modeling: you've read Kimball (or absorbed the equivalent), know the difference between star and snowflake schemas by feel, understand slowly changing dimensions, and can explain why a fact table's grain matters.
• Stakeholder management: demonstrated experience partnering with non-technical stakeholders, driving metric alignment, and delivering trusted data products — not just pipelines.
• Strong written communication: your documentation and async updates are clear enough that people don't need to ask follow-up questions.

Strong plus

• Experience with financial data or billing data — ARR, usage-based billing, invoice reconciliation, revenue recognition patterns. We operate a usage-based inference billing system and this context transfers directly.
• Experience with PII handling, data masking, access-tier modeling, or compliance work (SOC 2, ISO 27001, GDPR, CCPA).
• Familiarity with lakehouse patterns (Iceberg, Delta, Hudi) and hybrid warehouse/lake architectures.
• Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.
• Experience with Hex, Metabase, or similar notebook/BI tooling that sits on top of your dbt models.
• Prior experience in a high-growth AI/ML infrastructure or platform company.

Responsibilities

Modeling & transformation

• Own and evolve the dbt transformation layer: design, implement, test, document, and maintain modular dbt projects that cover billing, product usage, financial data, and operational metrics.
• Build analytics-ready dimensional models following Kimball methodology: star schemas, conformed dimensions, fact tables with the right grain, and SCD Type 2 for slowly changing entities.
• Design for correctness, performance, and cost — partition strategies, incremental models, and avoiding full-table scans.
• Build and maintain a semantic/metrics layer with consistent, auditable metric definitions reused across notebooks, BI, and APIs.

Pipeline orchestration

• Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate dbt runs, data quality checks, and downstream dependencies reliably.
• Apply solid DAG design: idempotent tasks, proper backfill strategies, SLA alerting, and clean dependency graphs.
• Work in our Cosmos (dbt + Airflow) integration — you know when to use a DbtTaskGroup vs a custom operator.

Data quality & governance

• Implement data quality checks at every layer: freshness, null/uniqueness tests, referential integrity, distribution drift, and business-rule assertions.
• Drive data stewardship practices: ownership, SLAs, clear "source of truth" definitions, and change communication.
• Handle PII fields correctly — masking, anonymization, and access-tier alignment. Compliance experience (SOC 2, ISO 27001, or similar) is a meaningful plus.

Stakeholder management

• Be the analytical partner to Finance, GTM, Product, and Engineering — translate business questions into durable data models, not one-off queries.
• Drive alignment on metric definitions, data ownership, and delivery tradeoffs across stakeholders with competing priorities.
• Communicate data quality issues, model changes, and breaking changes proactively. You treat downstream consumers as customers.
• Write clear documentation — model descriptions, column-level lineage, and business context — so analysts can self-serve with confidence.
• Run or contribute to data reviews, data-driven planning discussions, and architecture reviews involving the warehouse.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $240,000 - $275,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

Requirements

• Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
• Knowledge of ML/AI applications and models
• Knowledge of performance profiling and optimization tools for GPU programming
• Excellent problem-solving and analytical skills
• Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences

Responsibilities

• Optimize and fine-tune GPU code to achieve better performance and scalability
• Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
• Stay up-to-date with the latest advancements in GPU programming techniques and technologies

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

The Opportunity

Join a new engineering team in San Francisco building Flexport’s client-facing rates platform and self-serve freight booking experience from the ground up. You will work alongside experienced engineers and have direct ownership of features that move the company from an assisted-sales model to a tech-run one for the long tail of our client base.

This team owns two of the highest-leverage surfaces in the Client App: how clients see pricing and how they book without manual intervention. Rates sit at the center of every freight decision, and you will build the systems that power rate visibility, quoting, and pricing intelligence across ocean, air, and trucking. You will also help build the infrastructure that integrates AI-powered automation into the booking flow. This is a rare opportunity to build the "front door" of an $8.6 trillion industry, turning the complexity of global trade into a seamless digital experience for thousands of shippers.

You Will

• Design, develop, test, deploy, and maintain systems within a microservices architecture that power rate visibility and autonomous booking.
• Own the entire lifecycle of a feature: from database schema design and scalable backend APIs to building the React-based frontend applications our customers use.
• Support the integration of AI models and automated workflows to make the pricing and booking experience increasingly intelligent.
• Collaborate with engineering, product, and design to translate complex business problems into elegant, production-ready technical solutions.
• Contribute to code reviews to maintain high quality standards, share knowledge, and mentor peer engineers.
• Build highly available, secure, and distributed systems that can scale with Flexport’s global volume.
• Rapidly build and launch products incrementally, leveraging best practices around CI/CD and shipping to production dozens of times per day.
• Ensure high-quality standards by incorporating metrics, monitoring, and applying learnings from post-mortems to all services.

You Should Have

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
• 3+ years of professional software engineering experience with a proven track record of shipping production-grade applications.
• Full-Stack Capability: You are comfortable owning a feature from end-to-end: working with databases, backend services (Java/Ruby), and frontend frameworks (React).
• Technical Rigor: A passion for simple, well-tested code that is easy to extend and hard to break.
• AI Familiarity: Experience or interest in working with AI APIs and building software that leverages machine learning models to automate user tasks.
• 2+ years of design and architecture knowledge as well as familiarity with object-oriented analysis and design patterns.
• Proficiency with modern programming languages: specifically Java, Ruby, or TypeScript.
• Proficiency with deploying, monitoring, and maintaining production services on cloud infrastructure (AWS).

It’s a Plus If You Have

• Experience with elements of our tech stack: Java, Spring Boot, Ruby on Rails, React, AWS.
• Experience in fintech, pricing engines, or booking systems.
• Experience in logistics, supply chain, or freight technology.
• A bias for action: When you see a problem, you fix it.
• Excellent written and verbal communication skills: you can convey technical ideas in common terms to business stakeholders and product managers.

#LI-onsite

Secure Every Identity, from AI to Human

Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

Okta is looking for an experienced Director of Partner Programs to strategically architect,  implement, and manage a global partner program driving the company’s success while supporting multiple partner types. This person should have extensive experience leading program strategy, building and managing teams in a high growth SaaS environment.  This individual will use a data driven approach while incorporating partner feedback and internal feedback to continuously optimize the Okta Partner.  

Job Responsibilities & Duties:

• Design, implement, and manage a robust and competitive Partner Program structure that effectively supports and incentivizes multiple partner types (e.g., Distributors, GSIs, Resellers, Service Delivery Partners, System Integrators and Technology Partners) and supports Cloud Marketplaces.
• Lead the design and execution of partner programs across AMER, EMEA, and APJ regions.
• Serve as the strategic leader and primary point of contact for the global Partner team, driving initiatives for the continued evolution and success of the Okta Partner Program.
• Develop and drive the long-term partner program strategy, requirements, and policy across the entire partner lifecycle, from recruitment to performance management.
• Direct and mentor the Partner Program team, focusing on organizational design to support growth, scale, and effective prioritization aligned with long-term program goals.
• Define and govern the framework for partner tiering, benefits, incentives, and requirements to ensure program value and growth.
• Collaborate with Partner Experience and Ops team to integrate AI and automation to create a self-service environment for partners, reducing time-to-value (Operational Excellence).
• Lead cross-functional engagements with internal stakeholders (Sales, Marketing, Legal, Finance, Product, Operations, and Systems ) to resolve complex business issues, define long-term program strategy, identify optimization opportunities and set policy for partner engagement. This role will serve as the central link between the partner organization and these teams, and requires the ability to effectively influence and build consensus with cross-functional leadership.
• Provide clear, concise, and compelling communication to executive leadership on program strategy, performance, and risks, ensuring transparency and timely decision-making.
• Monitor and report on global Partner Program performance, ensuring accountability for annual performance reviews and program effectiveness. This includes building global dashboards to act as a "Single Source of Truth" for partner performance (Data Leadership).
• Oversee and provide requirements for the successful integration of program features into partner tools (PRM, CMS, etc.) in collaboration with Partner Operations.

Required Skills & Qualifications:

• Minimum 10+ years of progressive work experience in a high-growth SaaS company (Cybersecurity preferred), with at least 3 years in a leadership role focused on Partner Program Strategy and Management across multiple geographies.
• A proven track record of scaling partner programs during massive growth phases.
• Strong experience in designing, launching, and managing successful global partner programs that support diverse partner ecosystems (e.g., Distributors, GSIs, Resellers, MSPs, Service Delivery Partners, System Integrators, and Technology Partners.
• Proven expertise in leveraging major Cloud Marketplaces (e.g., AWS, Azure, GCP) as a scalable route-to-market and growth engine.
• Highly organized, detailed oriented and capable of managing and prioritizing multiple complex, simultaneous projects.
• Expertise in partner legal frameworks and executing adoption-focused strategies within the partner ecosystem.
• Outstanding verbal and written communication skills with proven project management proficiency. 
• Highly motivated self-starter and excellent problem solver via collaboration.
• Demonstrated experience working cross-functionally across organizations.
• Exceptional integrity, business acumen and sound judgement.
• Highly collaborative and committed to incorporating diverse perspectives and feedback into strategy and execution.
• Comfortable with travel up to 10%.
• BA/BS degree required; MBA or relevant Masters degree strongly preferred.

• Help design, train, with a focus towards deploying onboard machine learning models that improve the performance/latency of the Kodiak autonomy stack which includes quantization, pruning, converting to ONNX/TensorRT, custom GPU kernels and profiling.
• Help identify and achieve parity between onboard and deployed offboard models using validation on HIL 
• Collaborate with cross-functional teams including perception, planning, simulation, and autonomy infrastructure to integrate ML models into production systems.
• Analyze real-world driving logs to identify edge cases and improve model robustness and safety.
• Use profiling tooling to additionally help improve the train time for models by identifying and removing bottlenecks.
• Contribute to the development of scalable AI infrastructure that supports continuous learning and deployment across Kodiak’s fleet.

• MS or PhD in Computer Science, Robotics, Machine Learning, or a related technical field, or equivalent practical experience.
• 6+ years experience deploying machine learning or deep learning systems in production environments.
• Proficiency in Python, C++ and modern ML frameworks such as PyTorch or TensorFlow.
• Experience working with large-scale distributed training systems.
• Solid understanding of optimization, and machine learning fundamentals.
• Strong software engineering fundamentals including testing, debugging, and system design.
• Ability to work collaboratively across teams to solve complex autonomy and robotics challenges.

What we offer:

• Competitive compensation package including equity and annual bonuses
• Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and  MetLife (including a medical plan with infertility benefits)
• MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
• Flexible PTO, 10 paid holidays, and generous parental leave policies
• Our office is centrally located in Mountain View, CA
• Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
• Long Term Disability, Short Term Disability, Life Insurance
• Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation) 
• Fidelity 401(k)
• Commuter, FSA, Dependent Care FSA, HSA
• Various incentive programs (referral bonuses, patent bonuses, etc.)

What We're Looking For

As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure.
You will partner with customers to design and deploy end-to-end AI systems, spanning:

• Model development and training
• GPU infrastructure and cluster design
• Distributed inference and production deployment

This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.

The role can be based out of our New York City or San Francisco office, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time. The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity. 

What You’ll Do

Customer Architecture & Technical Leadership

• Partner with customers to understand ML workloads, infrastructure constraints, and scaling requirements
  
  
• Architect end-to-end solutions across:
  
  
• Data pipelines (CPU → GPU workflows)
  
  
• Distributed training (multi-node, multi-GPU)
  
  
• High-throughput inference systems
  
  
• Translate business goals (latency, cost, throughput) into technical system design decisions
  
  

GPU & Infrastructure Design

• Design and optimize workloads across GPU clusters (H100, H200, B200, etc.)
  
  
• Advise on:
  
  
• Training vs inference cluster design
  
  
• Interconnect choices (Ethernet vs Infiniband / RDMA vs Roce)
  
  
• Storage strategies (local NVMe vs networked / object storage)
  
  
• Model and optimize for:
  
  
• Tokens/sec, tokens/$
  
  
• Throughput vs latency tradeoffs
  
  
• GPU utilization and scheduling efficiency
  
  

Kubernetes & Platform Systems

• Design and support deployments on Kubernetes (EKS, GKE, on-prem clusters)
  
  
• Work with:
  
  
• GPU scheduling (time-slicing, MIG, bin-packing)
  
  
• Autoscaling and workload orchestration
  
  
• Helm-based deployments and multi-tenant environments
  
  
• Help customers balance:
  
  
• Raw Kubernetes flexibility vs platform abstraction (Lightning)
  
  

Demos, POCs, and Execution

• Build and deliver technical demos and POCs that showcase:
  
  
• Distributed training workflows
  
  
• Scalable inference endpoints
  
  
• End-to-end ML pipelines on Lightning AI
  
  
• Scope and lead POCs aligned to customer success metrics (latency, cost, reliability)
  
  

Cross-Functional Impact

• Act as the bridge between customers, product, and engineering
  
  
• Provide feedback on:
  
  
• Platform gaps in infrastructure, orchestration, and performance
  
  
• Emerging patterns in GPU usage and distributed systems
  
  
• Influence roadmap across ML workflows and infrastructure capabilities
  
  

Enablement & Thought Leadership

• Create technical content
• Architecture guides (e.g., high-throughput LLM inference systems)
• Best practices for GPU utilization and scaling
• Educate customers on modern AI infrastructure patterns

What You’ll Need

ML + Systems Expertise

• 3–6+ years experience in:
  
  
• Machine Learning / AI Engineering
  
  
• Solutions Engineering / Sales Engineering / ML Consulting
  
  
• Strong understanding of:
  
  
• Training vs inference workloads
  
  
• Model optimization (quantization, batching, caching, etc.)
  
  

GPU & Distributed Systems

• Experience working with:
  
  
• GPU clusters (NVIDIA stack preferred)
  
  
• Distributed training or inference systems
  
  
• Familiarity with:
  
  
• NCCL, CUDA, or GPU performance profiling
  
  
• Networking concepts (RDMA, Roce, Infiniband, high-throughput systems)
  
  

Kubernetes & Cloud Platforms

• Hands-on experience with:
  
  
• Kubernetes (EKS, GKE, or on-prem)
• Slurm 
• Containerization (Docker)
  
  
• Exposure to:
  
  
• GPU scheduling in Kubernetes environments
  
  
• Multi-tenant or production ML deployments
  
  

Programming & Tooling

• Strong Python skills (PyTorch preferred)
  
  
• Experience building:
  
  
• ML pipelines
  
  
• APIs or inference services
  
  
• Familiarity with Lightning AI, PyTorch Lightning, or similar frameworks is a plus
  
  

Customer-Facing Excellence

• • Ability to:
    
    
    • Explain complex infrastructure and ML tradeoffs clearly
      
      
    • Run technical discovery and uncover quantifiable success metrics
      
      
  • Experience working cross-functionally with:
    
    
    • Sales, product, and engineering teams

What We're Looking For

Lightning AI is seeking a Senior Storage Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will focus on building and operating the storage systems that power large-scale AI/ML training, inference, and HPC workloads. You will work at the intersection of software, hardware, and operations—developing automation, improving reliability, and scaling distributed storage systems across our bare-metal infrastructure.

You will help own the data plane of our storage infrastructure, supporting high-throughput, low-latency data access for some of the most demanding AI workloads. You’ll play a key role in managing and evolving our storage stack (including VAST and S3-compatible systems like Ceph), ensuring performance, reliability, and efficiency at scale.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Storage Systems & Infrastructure

• Operate and scale distributed storage systems, including VAST and S3-compatible object storage (e.g., Ceph)
• Improve performance, reliability, and efficiency of storage systems supporting large-scale AI/ML workloads
• Troubleshoot complex storage and data path issues across hardware and software layers
• Optimize storage performance to support high-throughput, low-latency AI training and inference workloads

Automation & Tooling

• Build and maintain automation for provisioning, managing, and monitoring storage infrastructure
• Develop Python-based tools and workflows to reduce manual operational overhead
• Improve lifecycle management of storage clusters, from deployment through maintenance and scaling

Systems & Operations

• Manage and operate Linux-based systems in production, including bare-metal environments
• Partner with infrastructure and data center teams on hardware bring-up, upgrades, and issue resolution
• Support capacity planning, utilization tracking, and forecasting for storage systems
• Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability

Cross-Functional Collaboration

• Work closely with Infrastructure Engineering, Network Engineering, and Platform teams to integrate storage into the broader platform
• Contribute to design discussions around new infrastructure deployments and scaling strategies
• Help define best practices for operating storage systems in high-performance computing environments

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Hands-on experience operating distributed storage systems (e.g., VAST, Ceph, or similar)
• Strong Linux systems experience in production environments
• Proficiency in Python or similar scripting/programming languages for automation
• Experience working with bare-metal infrastructure and hardware-oriented systems
• Ability to debug complex issues across system boundaries (storage, OS, hardware, networking)
• Experience with storage networking protocols (e.g., NFS or similar)
• Experience with capacity planning, monitoring, and performance tuning

Ideal Experience

• Experience with VAST storage systems in production environments
• Experience operating S3-compatible object storage at scale
• Data center operations experience, including working with physical hardware
• Familiarity with AI/ML or HPC workloads and their storage requirements
• Background in high-performance or low-latency distributed systems
• Familiarity with high-performance data transfer technologies (e.g., RDMA, GPU Direct Storage)
• Experience supporting GPU-based workloads or large-scale compute clusters

Compensation

What We're Looking For

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software—developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads.

You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Systems, Image & Validation Infrastructure

• Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure
• Run and maintain test clusters used for system validation, diagnostics, and bring-up
• Validate firmware, drivers, and OS images across compute and GPU-enabled systems
• Support hardware qualification efforts for next-generation platforms

GPU Diagnostics & Performance

• Own GPU diagnostics and validation workflows across large-scale infrastructure
• Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
• Analyze system and GPU performance using tools such as NVIDIA DCGM
• Identify failure patterns and drive improvements in system stability and validation coverage

Automation & Tooling

• Build and maintain automation for provisioning, validation, and system bring-up
• Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
• Improve the reliability, repeatability, and scalability of image pipelines and validation systems

Systems & Operations

• Manage and operate Linux-based systems in production and validation environments
• Manage virtualization technology
• Support bare-metal provisioning workflows, including PXE and image-based systems
• Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging

Cross-Functional Collaboration

• Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
• Collaborate with platform and ML teams to ensure systems meet workload requirements
• Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Strong Linux systems experience in production environments
• Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM
• Familiarity with bare-metal provisioning and system bring-up workflows
• Proficiency in Python or similar scripting/programming languages for automation
• Ability to debug complex issues across hardware, OS, GPUs, and system software

Ideal Experience

• Experience with high-performance interconnects (e.g., InfiniBand, NVLink)
• Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows
• Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish
• Data center operations experience, including working with physical hardware
• Experience supporting AI/ML or HPC workloads at scale
• Experience with GPU validation frameworks or large-scale hardware qualification processes

Compensation

What We're Looking For

We’re looking for a Fullstack Engineer to help develop and scale the Lightning AI platform across the frontend, CLI, APIs, and core backend systems. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in React and either Python or Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Proficiency in React and either Go (Golang) or Python, with a preference for Go
• Strong understanding of software engineering principles and lifecycle
• Hands-on experience as a Fullstack Engineer in a SaaS technology company
• Proven ability to take ownership of key features and drive end-to-end development
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

What We're Looking For

We’re looking for a Backend Engineer to help develop and scale the Lightning AI platform, spanning APIs, infrastructure, billing, security, and integrations. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Extensive experience writing efficient, maintainable code in Go. Familiarity with best practices in testing, readability, and optimization is essential.
• Broad knowledge of backend and frontend systems, with experience building and scaling APIs, CLI tools, billing systems, and security protocols. Exposure to frontend frameworks is a plus.
• Experience with cloud platforms like AWS, GCP, or Azure and designing systems that are reliable, performant, and scalable. Familiarity with containerization (Docker, Kubernetes) is a strong advantage.
• Proven ability to take ownership of key features and drive end-to-end development
• Commitment to software quality, test automation, and continuous delivery. Experience proactively managing technical debt and speeding up time to production.
• Hands-on experience as a backend or product engineer in a SaaS technology company
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

About the team & opportunity 

*This is a hybrid position located in the Bay Area; the expectation is to go into the San Francisco office 2 times per week.

What’s so great about working on Calendly’s Product team?

We design seamless product experiences that delight our customers. Calendly takes the work out of scheduling so our customers have more time to focus on what matters most. Millions of people worldwide use our software every day—with thousands more signing up daily.

As a Staff Product Manager on the Scheduling team, you’ll be working on an incredible opportunity to evolve and scale a category-defining product while ushering it into the AI era. You’ll help ensure Calendly stays the most intuitive, powerful scheduling platform in the world, while leveraging AI to make it smarter, more proactive, and even more effortless for customers.

A day in the life of a Staff Product Manager at Calendly

This position will report to our Senior Director of Product. You will be working in an environment where collaboration is key to the best ideas, and you will be encouraged to use your creativity and drive to bring new features and ideas to market! You will work closely with engineering, design, sales, product marketing, customer experience and product leadership to ensure our defined growth, product/business outcomes, and customer satisfaction goals are met.

On a typical day, you will be working on: 

• Understanding customer needs, crafting a strategic product roadmap, and leading execution for one of our newest product initiatives
• Prioritizing feature requirements and partnering cross-functionally with R&D stakeholders (Design, Research, Engineering) to build a new 0-to-1 product
• Partnering closely with our go-to-market teams (marketing, customer success, sales, finance) to ensure successful product launches across multiple customer segments
• Driving up awareness, adoption, continual engagement and retention of new use cases that unlock more product capabilities within Calendly
• Defining and measuring the relevant objectives and key results (OKRs) and key performance measures to support strategy and roadmap decisions

What do we need from you?

• A minimum of 8-10 years of varied PM experiences across both startups and scaled companies; bonus points if you have been a founder in a SaaS company
• Keen product sense, UX design experience with a deep empathy for customers; highly motivated to build delightful and frictionless experiences for customers; bonus if you have used AI/ML to bring these experiences to life
• Experience in building 0-to-1 SaaS products and scaling from 1-to-100 in a product-led-growth environment
• Deep understanding and demonstrated experience building and monetizing teams-based productivity solutions in either a B2C or B2B
• The ability to work in our San Francisco office 2 days per week
• Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

Role Overview

Zeta Global is seeking a Lead Software Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows.

This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability.

The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments.

What You’ll Build

• Full-stack applications supporting HCP and patient (DTC) audience discovery, segmentation, and activation
  • Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
  • Identity resolution and data linkage services across fragmented data sources
  • Reporting, attribution, and measurement systems connecting campaigns to outcomes
  • APIs and services enabling downstream activation, analytics, and partner integrations

Key Responsibilities

• Lead architecture and hands-on development of distributed systems supporting healthcare data workflows
  • Design and implement scalable data pipelines (batch and streaming) for large-scale datasets
  • Build and maintain APIs and services with strong SLAs, observability, and fault tolerance
  • Implement identity resolution logic including matching, deduplication, and graph-based linkage
  • Ensure high data quality through validation, reconciliation, and monitoring frameworks
  • Design systems with strong security controls, including encryption, access control, and auditability
  • Apply privacy-by-design principles across all systems handling PHI/PII
  • Partner with Product and Data teams to translate healthcare requirements into scalable architectures
  • Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
  • Mentor engineers and act as a technical leader across the team

Engineering Expectations

• Strong experience designing distributed systems (microservices, event-driven architectures)
  • Deep understanding of data modeling, storage systems (OLTP, OLAP), and data processing frameworks
  • Experience with streaming and batch processing (e.g., Kafka, Spark, Flink, or similar)
  • Proficiency in backend development (Python, Java, or Ruby) and API design (REST/gRPC)
  • Experience building modern front-end applications (React or similar)
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
  • Familiarity with containerization and orchestration (Docker, Kubernetes)
  • Experience implementing observability (logging, metrics, tracing) and reliability patterns
  • Strong understanding of performance optimization and scalability tradeoffs

Healthcare & Domain Expectations

• Experience working with HCP data (provider identity, targeting, segmentation)
  • Experience with patient / DTC data workflows and privacy-aware systems
  • Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
  • Familiarity with identity graphs and data onboarding patterns
  • Experience building reporting or attribution systems tied to business outcomes
  • Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements

Qualifications

• 8–10 years of software engineering experience with increasing technical ownership
  • Proven track record of building and scaling data-intensive or distributed systems
  • Experience working in regulated environments (healthcare strongly preferred)
  • Strong system design and architecture skills
  • Ability to lead technically while remaining hands-on in implementation
  • Strong collaboration skills across engineering, product, and data teams

Preferred

• Experience with healthcare data providers or identity ecosystems
  • Background in AdTech, MarTech, or audience/data platforms
  • Experience with privacy-enhancing technologies (tokenization, clean rooms)
  • Exposure to ML/AI-driven data products or analytics systems

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $215,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-TS1

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

Role Overview

Zeta Global is seeking a Lead Software Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows.

This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability.

The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments.

What You’ll Build

• Full-stack applications supporting HCP and patient (DTC) audience discovery, segmentation, and activation
  • Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
  • Identity resolution and data linkage services across fragmented data sources
  • Reporting, attribution, and measurement systems connecting campaigns to outcomes
  • APIs and services enabling downstream activation, analytics, and partner integrations

Key Responsibilities

• Lead architecture and hands-on development of distributed systems supporting healthcare data workflows
  • Design and implement scalable data pipelines (batch and streaming) for large-scale datasets
  • Build and maintain APIs and services with strong SLAs, observability, and fault tolerance
  • Implement identity resolution logic including matching, deduplication, and graph-based linkage
  • Ensure high data quality through validation, reconciliation, and monitoring frameworks
  • Design systems with strong security controls, including encryption, access control, and auditability
  • Apply privacy-by-design principles across all systems handling PHI/PII
  • Partner with Product and Data teams to translate healthcare requirements into scalable architectures
  • Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
  • Mentor engineers and act as a technical leader across the team

Engineering Expectations

• Strong experience designing distributed systems (microservices, event-driven architectures)
  • Deep understanding of data modeling, storage systems (OLTP, OLAP), and data processing frameworks
  • Experience with streaming and batch processing (e.g., Kafka, Spark, Flink, or similar)
  • Proficiency in backend development (Python, Java, or Ruby) and API design (REST/gRPC)
  • Experience building modern front-end applications (React or similar)
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
  • Familiarity with containerization and orchestration (Docker, Kubernetes)
  • Experience implementing observability (logging, metrics, tracing) and reliability patterns
  • Strong understanding of performance optimization and scalability tradeoffs

Healthcare & Domain Expectations

• Experience working with HCP data (provider identity, targeting, segmentation)
  • Experience with patient / DTC data workflows and privacy-aware systems
  • Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
  • Familiarity with identity graphs and data onboarding patterns
  • Experience building reporting or attribution systems tied to business outcomes
  • Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements

Qualifications

• 8–10 years of software engineering experience with increasing technical ownership
  • Proven track record of building and scaling data-intensive or distributed systems
  • Experience working in regulated environments (healthcare strongly preferred)
  • Strong system design and architecture skills
  • Ability to lead technically while remaining hands-on in implementation
  • Strong collaboration skills across engineering, product, and data teams

Preferred

• Experience with healthcare data providers or identity ecosystems
  • Background in AdTech, MarTech, or audience/data platforms
  • Experience with privacy-enhancing technologies (tokenization, clean rooms)
  • Exposure to ML/AI-driven data products or analytics systems

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $215,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-TS1

We are looking for a Senior Software Engineer specializing in Machine Learning to join our Revenue ML team at Discord. This team partners with our revenue product groups, focusing on both consumer revenue and our emerging Ads initiative. This role will specifically contribute to our Ads ML efforts, helping to build and scale ML capabilities in areas such as ads measurement, targeting, and delivery ranking.

As part of this team, you will play a critical role in developing foundational ML models that enhance ad relevance, optimize performance, and drive revenue. This is a unique opportunity to work on an early-stage Ads ML platform and have a direct impact on the business's success. Our tech stack includes Python, ML frameworks like PyTorch and TensorFlow, large-scale data infrastructure, and real-time ad-serving technologies.

What You'll Be Doing:

• Design, develop, and deploy machine learning models for ads targeting and ranking.
• Develop sophisticated ML solutions such as identity graph to enhance ad targeting.
• Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, link click).
• Improve ads targeting and ranking by leveraging both on-platform and off-platform signals.
• Collaborate cross-functionally with product, engineering, and business teams to define and execute on the Ads ML roadmap.
• Scale our ML infrastructure to support an increasing number of concurrent ad campaigns while ensuring low-latency decision-making.
• Drive research and implementation of state-of-the-art ML techniques in the field of online advertising.

What You Should Have:

• 5+ years of experience as a Machine Learning Engineer or Data Scientist.
• 3+ years of experience specifically in Ads ML (ads ranking, personalization, optimization, privacy-compliant user modeling, targeting, or measurement).
• Strong proficiency in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with applied deep learning (e.g transformers, embedding models).
• Proven track record of designing, implementing, and scaling ML-driven ad systems in real-world applications.
• Experience working with real-time ML inference, A/B testing, and optimization frameworks.
• Experience translating ML evaluation results and performance metrics into actionable product roadmap items.
• Ability to connect business objectives to ML solutions, with the flexibility to shift focus toward the highest-impact problems as priorities evolve.

Bonus Skills:

• Strong understanding of performance advertising and how ML impacts revenue and advertiser retention.
• Knowledge of ad tech industry standards and ads ecosystem including targeting, retrieval, ranking, pacing, frequency, auction, etc.
• Experience with large-scale recommendation systems.
• Experience with large-scale data infrastructure and distributed computing

The US base salary range for this full-time position is $220,000 to $247,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

The role

As a Nebius BDR, you will be the first point of contact for leading companies across America exploring next-generation cloud and AI solutions. Working closely with Account Executives, Marketing, and Product teams, you will build and qualify pipeline to accelerate Nebius’s growth in US markets.

You’re welcome to work remotely from the US - SF Bay Area, NYC, Austin TX or Boston.

Your responsibilities will include: 

• Territory & Account Penetration
  Collaborate with AEs to map and prioritize target accounts across America, then execute a mix of outbound calls, personalized emails, and LinkedIn outreach to secure qualified meetings.
• Inbound Lead Qualification
  Screen and qualify inbound MQLs generated by Marketing, ensuring each prospect meets BANT criteria before handing off a detailed prospect brief to AEs.
• Customer & Market Engagement
  Conduct qualification calls to uncover customer pain points, technical requirements, and budget. You’ll also represent Nebius at key American tech events, book on-site meetings, and follow up to maximize ROI.
• Feedback & Continuous Improvement
  Gather market intelligence (common objections, competitive insights, feature requests) during prospect conversations and share it with Product and Marketing. Monitor outreach metrics—open rates, reply rates, connect rates—and collaborate with Sales Ops to optimize cadences and scripts. Stay up to date on AI and cloud trends (e.g., generative AI in pharma R&D) to position Nebius’s value proposition effectively.

We expect you to have: 

• 2+ years of SDR/BDR experience in cloud, B2B SaaS, or AI, with a proven track record targeting American markets.
• Ability to explain complex technical concepts (AI architectures, ML workflows) to both technical and non-technical stakeholders. 
• Highly self-motivated, goal-oriented, and able to thrive in a fast-paced startup environment.
• Excellent written and verbal communication skills, with strong cross-cultural awareness and adaptability. Collaborative team player comfortable operating in a hybrid office model.

It will be an added bonus if you have: 

• Familiarity with HubSpot CRM and sales engagement tools such as Outreach.

Key employee benefits:

• Health insurance: 100% company-paid medical, dental and vision coverage for employees and families.
• 401(k) plan: Up to 4% company match with immediate vesting.
• Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
• Remote work reimbursement: Up to $85/month for mobile and internet.
• Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.

Compensation

Base Salary of $95,000 with an OTE of $118,000

Join Nebius today!

This is a hybrid role that will sit out of our San Francisco office. Hybrid in-office Tuesdays and Wednesdays of each week. 

About the Role

We are looking for a builder to help lead our ‘AI for Work’ efforts. Together with the Director of AI Strategy and Enablement, you will build the internal AI infrastructure that makes our teams more efficient. That means building, evaluating vendors, and continuously evolving the AI systems our teams run on with the goal of maximizing every person's efficiency and scaling our ability to deploy agents across the business. You will embed directly within business functions across the organization, deeply understand how teams operate today, and fundamentally reimagine how they should operate tomorrow. This is not about bolting automation onto existing processes; it's about redesigning how work gets done with agentic tooling transforming (and eliminating) workflows. You will partner with leaders across the business to surface high-impact opportunities, architect intelligent solutions, and deliver measurable gains in productivity, output quality, and the experiences we deliver to our employees. You will define what "AI-native operations" looks like inside Taskrabbit. 

As the AI Productivity and Business Automation Lead, you will also own a critical role in scouting, evaluating, testing, and piloting third-party AI tools to unlock significant productivity gains across Taskrabbit. You’ll work closely with the Director of AI Strategy and Enablement and functional leads to map high-value process bottlenecks and identify AI solutions. You’ll also help create structured experiments and pilot programs that demonstrate measurable business impact. In addition, you’ll help bring cutting-edge AI technology into practical application, supporting implementation and tracking success to drive our AI Strategic Plan. 

You will be responsible for "mining" the business for efficiency opportunities while simultaneously helping to build the centralized orchestration layer that ensures our enterprise AI spend is governed, consistent, and scalable. This is a high-impact IC role designed for a "scrappy builder" who thrives on turning internal complexity into streamlined, automated excellence. 

What You Will Do: 

• Partner multiple functional leaders to define new standards for how teams operate in an AI-augmented environment. Reporting to the Director of AI Strategy and Enablement, you will establish the "AI-first" baseline for daily execution, ensuring that ways of working are clearly defined and consistent across all non-engineering functions. 
• Conduct structured discovery, shadowing teams, interviewing stakeholders, and mapping end-to-end processes, to identify where AI can eliminate, redesign, or dramatically accelerate work 
• Embed within internal business functions to develop a deep, firsthand understanding of current workflows, pain points, and decision-making processes to map high-value process bottlenecks. 
• Reimagine workflows from first principles rather than automating existing steps; challenge assumptions about what requires human involvement and what doesn't
• Design, build, and deploy AI-powered automations, agents, and internal tools that reduce time spent on repetitive, low-value-add tasks while improving the quality and consistency of outputs 
• Integrate large language models, agentic frameworks, and automation platforms into internal workflows with appropriate guardrails, error handling, and human-in-the-loop checkpoints
• Measure everything: establish baselines before intervention, track adoption and usage patterns post-deployment, and quantify productivity impact in terms of hours saved, error rates reduced, and cycle times compressed 
• Serve as a trusted advisor to functional leaders on what AI can and cannot do for their teams; translate business problems into technical solutions and technical constraints into business language 
• Stay abreast of the rapidly evolving AI tooling landscape (e.g., LLM capabilities, orchestration frameworks, RPA-to-AI convergence, no-code/low-code platforms) and calibrate our internal stack accordingly 
• Build reusable patterns, templates, and playbooks so that successful automations in one function can be adapted and scaled across others 
• Collaborate closely with the engineering and product organizations to ensure internal automation efforts align with our broader technology strategy and do not create shadow IT risk 
• Help to define the framework for evaluating the success and health of our workforce transformation. You will determine the key signals that demonstrate progress, partnering with Finance and Data Science to ensure that operational shifts deliver validated value to Taskrabbit. 
• You will focus on moving beyond tool adoption to fundamental change, ensuring our teams are positioned to focus on high-value, high-judgment work that drives enterprise performance. 
• Beyond individual projects, you will focus on helping to build the mindset and capability for teams to lead their own evolution. You will create the models that allow the organization to stay agile, ensuring the workforce can continuously adapt as technology and market conditions change. 

Skills Required: 

• Educational Foundation: You hold a Bachelor’s degree in Computer Science or a comparable technical field, with demonstrated interest in Business Analytics, Finance, Data Science, applied AI, or related disciplines. 
• Experience: You bring 5+ years of professional experience, including 1–2 years of direct, relevant experience in AI, data, or analytics-driven roles. 
• GenAI Fluency: You have hands-on experience with generative AI tools (e.g., Gemini, ChatGPT, Claude) through professional, academic, or personal projects, with a strong understanding of concepts such as state management and prompt versioning. 
• AI & ML Knowledge: You possess a solid understanding of AI technologies and machine learning concepts, and can apply them effectively in business contexts.
• Analytical Thinking: You demonstrate a strong analytical mindset, with the ability to design experiments, interpret metrics, and distinguish meaningful signals from noise.
• Communication Skills: You communicate clearly and concisely, translating complex technical insights into actionable recommendations for non-technical stakeholders.
• Ownership & Drive: You exhibit curiosity, a bias for action, and a strong sense of ownership in fast-moving, ambiguous environments. 
• Hands-on Builder Mindset: You are a scrappy, execution-oriented builder who can take ideas from stakeholders and independently develop working agentic workflows without relying on external engineering resources. 
• Business Acumen: You translate complex AI capabilities into clear business value, articulating ROI and impact for diverse stakeholders. 
• Operational Excellence: You bring rigor to operations, including managing vendor relationships, forecasting technical costs (e.g., token usage), and maintaining system reliability and SLAs. 
• Strategic AI Perspective: You stay current with rapid advancements in AI (e.g., LLMs, agents), proactively identifying implications for business and workforce transformation. You effectively bridge the gap between what is technically possible and what is practically scalable. 
• Leadership & Influence: You are a self-starter who thrives in ambiguity and can lead high-stakes discussions with senior leaders, using structured thinking and compelling storytelling to drive alignment and change. 
• Impact Orientation: You are deeply data-driven, partnering effectively with Finance and Data Science to define success metrics and ensure initiatives deliver measurable productivity gains and business impact. 
• Continuous Learning: You demonstrate strong intellectual curiosity and a commitment to continuous learning, staying ahead of emerging technologies to ensure long-term organizational readiness.

Compensation & Benefits: 

At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks. The base pay range for this position is $192,000 - $250,000. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level.

We are looking for a Senior Data Engineer to join our Data & ML Platform team, responsible for development, maintenance and support for Oura’s Datalake and adjacent systems, collaborating closely with data scientists, analysts and other departments utilizing the Datalake.

This is a hybrid role based in San Francisco, CA, working onsite 1-2 days per week.

We have offices in San Francisco, San Diego and Los Angeles for those who prefer hybrid or office settings. Oura employees in other major cities (like Boston and New York) occasionally gather informally at local co-working locations.

What you will do: 

• Build, operate, and improve Oura’s Datalake consisting of systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as AWS Kinesis, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
• Design and implement data models and pipelines with a strong focus on data quality, reliability, and governance.
• Ensure that our data platform and processes meet privacy, compliance, and security requirements.
• Build components that support the handling of datasets, training, testing, and release of new on-device and cloud-based ML models.
• Independently collaborate with different stakeholders including Data Scientists, Testing, Firmware, and Hardware to define and implement improvements and new functionality and support internal Datalake consumers in their day-to-day work.
• Write code, mostly in Python and SQL  with occasional additions Typescript, Java or some other language.

We would love to have you on our team if you have:

• 5+ years of experience developing and operating production systems.
• Experience running, monitoring, and debugging production systems at scale on a public cloud. We rely on AWS but experience with other cloud platforms counts too.
• Good architectural understanding of event-driven architectures, workflow engines, database, and data warehouse systems.
• Ability to design robust data models and pipelines, with attention to data accuracy and integrity.
• Experience in building infrastructure and components following best practices such as CI/CD and infrastructure as code.
• Demonstrated skills in writing well-structured, testable, and high-performance code.
• Familiarity with some of the following: Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks.
• You are self-motivated, proactive, and able to lead and manage your own work effectively.
• A pragmatic and goal oriented approach to development.

What Makes You Stand Out

• Real-life experience with Databricks.
• Familiarity and experience with the Data Mesh approach
• Broad knowledge of software fundamentals, databases, warehouses, and system design with experience on various programming languages

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1 $172,550 - $203,000
• Region 2 $159,000 - $187,000
• Region 3 $148,000 - $174,000

A recruiter can determine your zones/tiers based on your US location.

Responsibilities:

• Maintain full ownership of pipeline generating activities in your sales territory
• Collaborate with sales teams to understand their needs and optimize lead handoff processes
• Manage and prioritize a high volume of inbound leads
• Conduct initial qualifications for high-potential leads
• Outbound against strategic prospects to generate high-intent opportunities with Startup and Enterprise teams
• Support the development and execution of strategic outbound initiatives
• Provide data-driven insights to inform sales strategies and resource allocation
• Continuously refine processes to improve efficiency and effectiveness

You may be a good fit if you have:

• 3+ years of experience in a fast-growing startup, preferably in lead management and project management roles or
• 3+ years of experience in finance & investment banking, consulting or software engineering
• Strong analytical skills with the ability to translate data into actionable insights
• Experience with Salesforce, HubSpot, and SQL (preferred)
• Excellent communication and interpersonal skills
• Ability to work in a fast-paced, dynamic environment
• Passion for AI/ML and understanding of API-first or consumption-based business models
• Bachelor's degree in Business, Marketing, Computer Science, or related field

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

AI & Partner Systems Strategy Manager 

At NICE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you. 

So, what’s the role all about? 

The AI & Partner Systems Strategy Manager leads the design, development, and deployment of AI-powered solutions that transform Partner Operations at scale.  This role focuses on building AI agents, intelligent workflows, automation frameworks, and advanced analytics.  that modernize operational processes, increase efficiency, and unlock data-driven decision making across the partner ecosystem.   

How will you make an impact  

• Lead AI‑driven transformation initiatives across Partner Operations, identifying manual, fragmented, or inefficient processes and redesigning them using AI, automation, and intelligent workflows 

• Design and implement AI agents that support partner onboarding, enablement, support, data enrichment, workflow orchestration, and operational decision making 

• Drive the technical strategy for intelligent automation, leveraging machine learning, generative AI, rules engines, and event‑driven architectures 

• Partner with Product Engineering, Data and Partner Operations teams to build, integrate, and deploy AI solutions using modern development practices and scalable architectures 

• Translate operational and business problems into clear technical requirements, system designs, and implementation roadmaps  

• Develop and maintain analytics frameworks and dashboards that provide deep visibility into partner operations, system performance, and AI effectiveness 

• Evaluate, prototype, and operationalize new AI technologies, frameworks, and platforms, ensuring security, scalability, observability, and data governance 

• Enable partner operation teams through AI‑driven insights, self‑service tools, and intelligent user experiences, reducing manual effort and cycle times 

• Leads the global strategy for modernizing the Partner Relationship Management (PRM) ecosystem, ensuring systems align with partner needs and future business requirements. Provides ongoing insights and recommendations based on partner feedback, system analytics, and market trends to drive continuous improvement.  

• Partners with readiness and enablement teams to ensure partners understand how to effectively use system tools and features. 

Have you got what it takes?  

• 5+ years of experience AI transformation, intelligent automation, systems strategy, product engineering, or enterprise technology.   

• Strong hands on or technical experience with AI, machine learning, automation, or agent-based systems 

•  Proficiency or working experience with C++ and Javascript, and familiarity with modern software development practices (APIs, event driven systems, microservices) 

• Experience designing or delivering AI-powered workflows, automation platforms, or analytics solutions in an enterprise environment. 

• Strong understanding of data pipelines, system integrations, and analytics architectures.   

• Proven ability to lead cross-functional technical initiatives Working effectively with Engineering, Data, Product, and Operations teams.  

• Excellent communication skills with the ability to translate technical concepts into clear business outcomes and operational value.   

• Strong analytical and problem-solving skills, with a passion for continuous optimization through data and AI.  

• Experience gathering business requirements and working with technical teams to deliver system enhancements. 

You will have an advantage if you also have: 

• Experience with Salesforce, partner portals, AI platforms, or workflow automation tools.  

• Background in partner ecosystems, channel management, or partner driven business models.  
• Certifications in product management, AI, project management, or system architecture (e.g., Salesforce, PMP, CSPO). 

What’s in it for you? 

Learn more about the Benefits at NICE (Link which we will land up on benefits section  

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr! 

Enjoy NICE-FLEX!  

At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. 

About NICE   

NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NICE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions. 

Known as an innovation powerhouse that excels in AI, cloud and digital, NICE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries. 

NICE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.  

Requisition ID:  
Reporting into: VP, Partner Strategy and Operations 

Role Type: Individual Contributor