Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell® Fusion, gathers sensor data from millions of IoT devices — including smartphones, proprietary Tags, connected vehicles, dashcams, and third-party devices — and fuses them with contextual data to create a unified view of vehicle and driver behavior. Auto insurers, automakers, commercial mobility companies, and the public sector use insights from CMT’s platform to power risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT measures and protects tens of millions of drivers across the world every day.

CMT is looking for a creative, collaborative, and highly motivated Machine Learning Intern to help develop applied machine learning capabilities using real-world mobility and behavioral data. This internship is ideal for someone who enjoys solving ambiguous problems, building practical ML workflows, working with messy real-world datasets, and translating technical findings into clear recommendations.

The intern will work on a 12-week applied ML project involving data exploration, labeling strategy, feature engineering, model development, evaluation, and stakeholder-facing analysis. The ideal candidate has strong Python skills, a solid foundation in machine learning, strong initiative, and the ability to make progress in open-ended problem spaces.

Responsibilities:

• Explore real-world mobility datasets and identify useful behavioral, temporal, contextual, and aggregate patterns
• Help define practical data labeling guidelines, quality criteria, and edge-case handling rules
• Build and validate datasets for supervised machine learning experiments
• Develop baseline and improved ML models using Python and standard data science workflows
• Perform feature engineering, model evaluation, error analysis, and iteration
• Assess model performance across relevant data segments and edge cases
• Summarize findings, limitations, risks, and opportunities for technical and product stakeholders
• Produce clear documentation, analysis reports, and final recommendations

Qualifications:

• Currently pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Data Science, Machine Learning, Statistics, Engineering, Applied Math, or a related quantitative field
• Strong Python programming skills and comfort working with real-world datasets
• Solid understanding of supervised machine learning, feature engineering, classification metrics, train/test splits, and error analysis
• Experience with common Python data science libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, or similar tools
• Strong analytical and problem-solving skills, with a bias toward initiative and ownership
• Clear written and verbal communication skills, including the ability to explain technical findings to non-technical stakeholders

Compensation and Benefits:

• Fair and competitive hourly rate based on education level
• Flexible scheduling options depending on role and responsibilities

Additional Perks:

• Feel great working to improve road safety around the world!
• Join one of our many employee resource groups including Black, AAPI, LGBTQIA+, Women, Book Club and Health & Wellness
• CMT will do all that is possible to support our employees and create a positive and inclusive work environment for all!

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

Job Title: GenAI Developer/ Engineer

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Location - Bangalore

Experience - 6 to 10

Skills and Qualifications:

Preferred skills:

Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)

GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel

Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities:

• Develop scalable Python applications focused on GenAI
• Knowledge of Snowflake Cortex is a big plus.
• Learn and apply techniques like document chunking and embeddings
• Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Follow coding best practices and contribute to testing and documentation
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.

ABOUT THE ROLE:

We are establishing a dedicated team of AI Engineers to serve as a long-term strategic AI partner to one of the most influential AI organizations in the Middle East, headquartered in the UAE. This team will work closely with a highly ambitious client operating at the forefront of AI adoption across the region, supporting a continuously evolving pipeline of AI-driven initiatives.

As a Principal AI Engineer, you will work directly with customer leadership, technical teams, and internal stakeholders to deeply understand complex use cases and design, build, and deploy impactful AI solutions. This role blends hands-on engineering, AI system design, and customer-facing strategy—similar in scope to a hands-on AI startup CTO.

Rather than supporting a single static product, you will work across multiple domains and initiatives as new opportunities emerge. The Middle East’s strong national investment in AI creates a unique environment where experimentation, ambition, and real-world impact are expected, not optional.

WHAT MAKES THIS ROLE UNIQUE:

• A long-term strategic partnership, not short-term consulting.
• Exposure to large-scale, high-impact AI initiatives across sectors such as government, healthcare, energy, smart cities, and advanced research.
• The opportunity to design and deploy AI systems in an environment prioritizing speed, innovation, and real-world outcomes.
• A high-trust, fast-moving setting where engineers have meaningful ownership and influence.

RESPONSIBILITIES:

Customer Engagement & AI Strategy

• Partner closely with client stakeholders to understand strategic objectives, technical requirements, and operational constraints.
• Act as a trusted advisor on AI strategy, helping customers identify, prioritize, and implement high-impact generative and agentic AI use cases.
• Lead workshops, technical deep dives, and brainstorming sessions to translate business needs into AI-driven solutions.

AI Solution Design & Delivery

• Design, prototype, and deploy AI-powered proofs of concept (PoCs) and production solutions using generative AI models, agentic systems, and LLM workflows.
• Build end-to-end AI pipelines, from data ingestion to deployment, ensuring scalability, security, and performance on modern infrastructure.
• Implement solutions using the latest AI models and techniques, driving tangible business outcomes for the client.

Iterative Prototyping & Experimentation

• Use an experiment-driven approach to rapidly test hypotheses, iterate on designs, and refine solutions in collaboration with client teams.
• Explore and apply cutting-edge techniques in areas such as NLP, computer vision, reinforcement learning, and multi-agent systems.
• Develop reusable frameworks, patterns, and tools to accelerate AI delivery across future initiatives.

Cross-Functional Collaboration

• Work closely with Sales, Solutions Engineering, Solutions Architects, Applied Research, Product, and Customer Success teams supporting the same account.
• Provide structured feedback from customer engagements to influence internal product and platform development.

Knowledge Sharing & Mentorship

• Document best practices, architectures, and lessons learned from deployments to strengthen internal delivery capabilities.
• Mentor junior engineers on applying generative and agentic AI technologies in real-world, enterprise environments.

REQUIREMENTS:

Technical Expertise

• Strong proficiency in Python and/or JavaScript, with experience using ML frameworks such as PyTorch or TensorFlow.
• Hands-on experience with generative AI models (e.g., GPT-4/5), LLM-based systems, agentic workflows, or reinforcement learning frameworks.
• Experience deploying AI/ML systems into production using cloud platforms (AWS, Azure) or on-premise infrastructure.

Problem Solving & Systems Thinking

• Proven ability to translate ambiguous business challenges into concrete, scalable AI solutions.
• Strong analytical skills to evaluate model performance and optimize systems for real-world constraints.

Client-Facing & Communication Skills

• Excellent communication skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders.
• Comfort operating in ambiguous, high-stakes environments while building trust-based client relationships.

Adaptability & Mindset

• Ability to work across multiple industries and domains, tailoring AI solutions to different contexts.
• Entrepreneurial mindset with a focus on ownership, execution, and measurable impact.
• Willingness to travel or work on-site with clients as required.

Education & Experience

• Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
• 3+ years of experience in software engineering, applied machine learning, or AI-focused roles.
• Prior experience working directly with customers on AI-driven applications is highly desirable.
• Passion for staying at the forefront of generative and agentic AI advancements and applying them pragmatically.

WHY THIS ROLE:

This role is ideal for engineers who thrive at the intersection of deep technical work, customer engagement, and real-world impact. As a Forward Deployed AI Engineer, you will help shape how AI is adopted at scale in one of the most ambitious and fast-growing AI regions globally—while growing alongside a client whose challenges and opportunities will continuously evolve.

BENEFITS

• You will work with amazing teammates from across Europe.
• Take a leading role in our newly-established Bulgarian center, contributing to the foundation of our future.
• Our Sofia office is right in the center, ensuring that everything you need is close by.
• Monthly transport allowance and enjoy the convenience of a dedicated parking area at the office.
• Enjoy 25 days of paid leave, we make sure you have plenty of time to relax and recharge.
• We’ve got you covered with additional premium health insurance and dental care, to keep you and your family protected.
• We offer food vouchers and to add a little extra you can enjoy complimentary meals in the office.
• Fully covered Multisport card that gives you access to a variety of fitness options to keep you active and feeling great.
• We support your growth with certifications and courses that help you advance your career.
• Join us for Social Events, Informal Office Gatherings and Team-building activities with your colleagues, where we celebrate our achievements together.
• We’ll work with you on an individual plan to help you reach your career goals.
• Benefit from our coaching and mentorship programs, technological and professional guilds that offer guidance and support for your career journey.
• Participate in various social initiatives, contributing to causes that matter to you.
• Use our online platform, dedicated to your well-being and mental health.
• Enjoy the flexibility of our Work Abroad Policy, letting you work from another European country for a period of time.
• Refer a Friend, Get Rewarded.

ABOUT THE ROLE:

We are establishing a dedicated team of AI Engineers to serve as a long-term strategic AI partner to one of the most influential AI organizations in the Middle East, headquartered in the UAE. This team will work closely with a highly ambitious client operating at the forefront of AI adoption across the region, supporting a continuously evolving pipeline of AI-driven initiatives.

As an Senior AI Engineer, you will work directly with customer leadership, technical teams, and internal stakeholders to deeply understand complex use cases and design, build, and deploy impactful AI solutions. This role blends hands-on engineering, AI system design, and customer-facing strategy—similar in scope to a hands-on AI startup CTO.

Rather than supporting a single static product, you will work across multiple domains and initiatives as new opportunities emerge. The Middle East’s strong national investment in AI creates a unique environment where experimentation, ambition, and real-world impact are expected, not optional.

WHAT MAKES THIS ROLE UNIQUE:

• A long-term strategic partnership, not short-term consulting.
• Exposure to large-scale, high-impact AI initiatives across sectors such as government, healthcare, energy, smart cities, and advanced research.
• The opportunity to design and deploy AI systems in an environment prioritizing speed, innovation, and real-world outcomes.
• A high-trust, fast-moving setting where engineers have meaningful ownership and influence.

RESPONSIBILITIES:

Customer Engagement & AI Strategy

• Partner closely with client stakeholders to understand strategic objectives, technical requirements, and operational constraints.
• Act as a trusted advisor on AI strategy, helping customers identify, prioritize, and implement high-impact generative and agentic AI use cases.
• Lead workshops, technical deep dives, and brainstorming sessions to translate business needs into AI-driven solutions.

AI Solution Design & Delivery

• Design, prototype, and deploy AI-powered proofs of concept (PoCs) and production solutions using generative AI models, agentic systems, and LLM workflows.
• Build end-to-end AI pipelines, from data ingestion to deployment, ensuring scalability, security, and performance on modern infrastructure.
• Implement solutions using the latest AI models and techniques, driving tangible business outcomes for the client.

Iterative Prototyping & Experimentation

• Use an experiment-driven approach to rapidly test hypotheses, iterate on designs, and refine solutions in collaboration with client teams.
• Explore and apply cutting-edge techniques in areas such as NLP, computer vision, reinforcement learning, and multi-agent systems.
• Develop reusable frameworks, patterns, and tools to accelerate AI delivery across future initiatives.

Cross-Functional Collaboration

• Work closely with Sales, Solutions Engineering, Solutions Architects, Applied Research, Product, and Customer Success teams supporting the same account.
• Provide structured feedback from customer engagements to influence internal product and platform development.

Knowledge Sharing & Mentorship

• Document best practices, architectures, and lessons learned from deployments to strengthen internal delivery capabilities.
• Mentor junior engineers on applying generative and agentic AI technologies in real-world, enterprise environments.

REQUIREMENTS:

Technical Expertise

• Strong proficiency in Python and/or JavaScript, with experience using ML frameworks such as PyTorch or TensorFlow.
• Hands-on experience with generative AI models (e.g., GPT-4/5), LLM-based systems, agentic workflows, or reinforcement learning frameworks.
• Experience deploying AI/ML systems into production using cloud platforms (AWS, Azure) or on-premise infrastructure.

Problem Solving & Systems Thinking

• Proven ability to translate ambiguous business challenges into concrete, scalable AI solutions.
• Strong analytical skills to evaluate model performance and optimize systems for real-world constraints.

Client-Facing & Communication Skills

• Excellent communication skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders.
• Comfort operating in ambiguous, high-stakes environments while building trust-based client relationships.

Adaptability & Mindset

• Ability to work across multiple industries and domains, tailoring AI solutions to different contexts.
• Entrepreneurial mindset with a focus on ownership, execution, and measurable impact.
• Willingness to travel or work on-site with clients as required.

Education & Experience

• Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
• 3+ years of experience in software engineering, applied machine learning, or AI-focused roles.
• Prior experience working directly with customers on AI-driven applications is highly desirable.
• Passion for staying at the forefront of generative and agentic AI advancements and applying them pragmatically.

WHY THIS ROLE:

This role is ideal for engineers who thrive at the intersection of deep technical work, customer engagement, and real-world impact. As a Senior AI Engineer, you will help shape how AI is adopted at scale in one of the most ambitious and fast-growing AI regions globally—while growing alongside a client whose challenges and opportunities will continuously evolve.

BENEFITS

• You will work with amazing teammates from across Europe.
• Take a leading role in our newly-established Bulgarian center, contributing to the foundation of our future.
• Our Sofia office is right in the center, ensuring that everything you need is close by.
• Monthly transport allowance and enjoy the convenience of a dedicated parking area at the office.
• Enjoy 25 days of paid leave, we make sure you have plenty of time to relax and recharge.
• We’ve got you covered with additional premium health insurance and dental care, to keep you and your family protected.
• We offer food vouchers and to add a little extra you can enjoy complimentary meals in the office.
• Fully covered Multisport card that gives you access to a variety of fitness options to keep you active and feeling great.
• We support your growth with certifications and courses that help you advance your career.
• Join us for Social Events, Informal Office Gatherings and Team-building activities with your colleagues, where we celebrate our achievements together.
• We’ll work with you on an individual plan to help you reach your career goals.
• Benefit from our coaching and mentorship programs, technological and professional guilds that offer guidance and support for your career journey.
• Participate in various social initiatives, contributing to causes that matter to you.
• Use our online platform, dedicated to your well-being and mental health.
• Enjoy the flexibility of our Work Abroad Policy, letting you work from another European country for a period of time.
• Refer a Friend, Get Rewarded.

About the Project
The platform uses AI agent architectures to generate and validate educational content at scale, serving multiple products across the organization. The team owns the end-to-end lifecycle: workflow design, LLM orchestration, evaluation, and production operations.

About the Role
We are looking for a senior AI engineer ready to work at the heart of production AI systems. You will  contribute directly to two core services: Conversation Brain, an LLM-driven conversation engine, and  Ambient ORA, a speech assessment engine powering multiple products. The role sits at the intersection of product engineering and AI science, bridging research outputs from the R&D team into production-grade services.

Key Responsibilities:

• Design, develop, and optimize AI-driven content generation workflows.
• Contribute directly to our codebases, building and maintaining agentic workflows using Python (FastAPI, CrewAI, LangGraph, LangChain) and Go where needed.
• Build and maintain agentic workflows using CrewAI, LangGraph, and LangChain.
• Ensure code quality through unit and integration tests written as part of the development workflow, in line with our shift-left approach where developers own test creation.
• Operationalize AI models in collaboration with the AI R&D.
• Implement LLM observability and evaluation using Langfuse, OpenLit, and New Relic.
• Design and run LLM evaluation benchmarks and regression detection.
• Integrate and manage resources across Azure (Container Apps, Service Bus, Blob Storage) and AWS.
• Ensure robust CI/CD pipelines and contribute to SDLC best practices.
• Package, deploy, and scale applications using Docker; Kubernetes experience is a plus.

Required Skills & Qualifications

• Strong Python development skills (FastAPI) and hands-on experience with agentic and LLM frameworks 
  (CrewAI, LangGraph, LangChain, or equivalent).
• Production experience with LLMs, including prompt engineering, model evaluation, and 
  operationalizing research outputs into production services (Azure OpenAI, Google Vertex AI).
• Practical experience with Azure services (Container Apps, Service Bus, Key Vault, Blob Storage) and 
  familiarity with AWS.
• Experience with LLM observability and monitoring tools (Langfuse, OpenLit, New Relic, or equivalent).
• Solid grasp of CI/CD, DevOps, and SDLC. Working knowledge of Docker, with k8s experience as a plus.
• Familiarity with ML/NLP tooling (PyTorch, Hugging Face Transformers, spaCy, scikit-learn) a strong plus.
• Daily user of AI development tools (Cursor, Claude Code, Copilot).
• Fluent English, spoken and written.
• Nice to have: Working knowledge of Go, with the ability to read, modify, and maintain existing Go 
  services

Benefits:

• Opportunities for certification and training
• Dual monitor setup and high-spec workstations
• English courses
• Gym allowance
• Medical Reimbursement
• Full salary covered up to 20 days of sickness
• Flexible working hours
• Loyalty scheme
• Team building activities, special events and conferences
• UK/EU Travel opportunities
• Snacks and drinks in the office

As a Machine Learning Engineer Intern at Optiver, you’ll work alongside experienced engineers on high-performing systems that respond to live financial markets in real time.

You’ll contribute to the compute platforms and libraries that support large-scale machine learning model training and simulation workloads, gaining hands-on experience applying modern ML techniques to real quantitative trading problems. Within weeks, you could be building tools or models that run in production and directly support our trading strategies.

By the end of the 8-week internship, you’ll have a clear and practical understanding of how technology and ML techniques are used in the quantitative trading industry. Plus, if you’ve excelled over the summer, you’ll receive an offer to return as a Machine Learning Engineer.

WHAT YOU’LL DO:

Led by our in-house education team that consists of ex-traders and engineers, you’ll delve into advanced engineering concepts and lead innovative projects, during our world-class training program.

In just a few weeks, you'll have the opportunity to:

• Gain first-hand experience applying the latest AI technology to quantitative trading problems.

• Help build the compute platform and libraries for large scale machine learning model training and simulation workloads.

• Manage a project end-to-end, learn how to work with a complex code base and make impactful contributions to production systems.

• Work on real trading and IT problems, both technically and functionally, to improve our trading success.

Throughout the program, you'll be paired with an experienced mentor, who will show you the ins-and-outs of our trading systems, and provide you with guidance and feedback.

Additionally, internal resources will be available for your continuous learning and development.

WHAT YOU’LL GET:

You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Driven by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the most complex problems in the financial markets.

In addition, you’ll receive:

• A highly competitive remuneration package.

• Optiver-covered flights and accommodation for the duration of the internship.

• The opportunity to work alongside best-in-class professionals.

• Training, mentorship and personal development opportunities.

• Gym membership, plus weekly in-house chair massages.

• Daily breakfast, lunch and in-house barista.

• Regular social events.
  
  

WHO YOU ARE:

• Students graduating in 2027 or later.

• Foundations in Machine Learning fundamentals, including optimisation and deep learning concepts.

• Hands-on experience with deep learning frameworks such as PyTorch, JAX, or similar.

• Interested in building scalable and reproducible machine learning pipelines, including data preprocessing, training, evaluation, and experiment tracking.

• Natural problem solvers who love nothing more than tackling a complex technical challenge.

• Team players who thrive in collaborative environments and are eager to learn, iterate, and improve.

• Interested in the trading / quantitative finance industry (prior finance knowledge is not required).
  
  Optional:

• Ability to identify and reason about compute and performance bottlenecks, using profiling, benchmarking, and systematic analysis to improve training efficiency.

• Experience with distributed training or GPU acceleration is a plus.

• Familiarity with experiment management tools (e.g. MLflow, Weights & Biases) or workflow orchestration is a plus.

HOW TO APPLY:

If you're ready to take the next step in your career and work on one of the most exciting trading floors in mainland China, we’d love to hear from you. Apply now via the form below. Applications close 16 March 2026.

In your application, please submit the following materials in English:

• Resume

• Cover letter (optional)

For any other inquiries, contact us at chinacareers@optiver.com.au

DIVERSITY STATEMENT

Optiver is committed to diversity and inclusion. We encourage applications from candidates of all backgrounds, and welcome requests for reasonable adjustments during the process.

We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can re-apply when the next recruitment season begins in 2027.

PRIVACY DISCLAIMER

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。

Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.

Responsibilities:

· Design, prototype, test, and deploy state-of-the-art behavior planning algorithms for autonomous and assisted driving features.

· Develop and implement decision-making, trajectory and route planning, and optimization-based planning frameworks.

· Collaborate closely with perception, controls, localization, and systems teams to ensure robust and efficient integration of planning software.

· Drive innovation through the invention of novel algorithms and features that elevate the safety, comfort, and intelligence of Lucid vehicles.

· Support the validation and verification of behavior planning components in simulation, hardware-in-the-loop (HIL), and on-road testing environments.

Required Qualifications:

· MS degree in Robotics, Computer Science, Aerospace Engineering, Mechanical Engineering, or a related field (or equivalent experience).

· 2+ years of professional experience, or a Ph.D. in a relevant discipline.

· Strong C++ programming skills with a solid understanding of software engineering best practices.

· Deep knowledge of decision-making algorithms such as graph/tree search methods or AI-based planners.

· Experience with motion and behavior planning concepts including decision-making under uncertainty, optimization techniques, trajectory generation, and route planning.

· Hands-on experience with embedded systems integration in robotics or automotive domains.

· Strong communication and problem-solving skills.

Preferred Qualifications:

· Experience with middleware systems such as ROS or DDS.

· Proficiency in scripting languages such as Python, Bash.

· Experience with simulation tools (e.g., Gazebo, CARLA) and frameworks for testing autonomous systems.

· Experience and understanding of deep learning frameworks (e.g., TensorFlow, PyTorch).

· Experience and knowledge of imitation/reinforcement learning techniques.

· Familiarity with version control systems (e.g., Git) and modern development workflows.

· Prior work on scenario-based testing, MIL/SIL/HIL environments, or automated test frameworks.

· Exposure to CI tools such as Jenkins or GitLab CI.

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.

WPP steht für kreative Transformation. Mit der Kraft von Kreativität gestalten wir eine bessere Zukunft für unsere Mitarbeitenden, unsere Kunden, unsere Gemeinschaften und unseren Planeten. Genau hier setzt WPP Media an: Als globales Mediennetzwerk von WPP vereinen wir die besten Plattformen, Talente und Partner, um in einer vernetzten Medienwelt neue Chancen für grenzenloses Wachstum zu schaffen.

Das bieten wir dir:

• Work-Life-Balance: Mit unseren flexiblen Arbeitszeiten & Remote Work gestaltest du deinen Alltag so, wie er zu dir passt. Außerdem kannst du Überstunden ausgleichen.
• Vacation mode on: Du erhältst 30 Urlaubstage plus einen flexiblen Tag – zusätzlich sind der 24. und 31.12. frei.
• Wellbeing first: Gesundheitsleistungen, attraktive Altersvorsorge sowie Mental Health Awareness Days stellen deine Gesundheit in den Mittelpunkt.
• Practice makes perfect: Entfalte dich mit unseren vielfältigen Weiterbildungen und nutze unsere internen Karriereprogramme für deine Entwicklung im WPP-Netzwerk.
• More than just a job: Dich erwarten unvergessliche Events, Mitarbeitendenrabatte und weitere Highlights wie das Job Ticket, Wellhub oder das Job Bike.
• Be yourself: Bei uns ist jede:r herzlich willkommen - Vielfalt und Chancengleichheit liegen uns am Herzen.

Das bewegst du:

Als Associate Director Data Science (Mensch) gestaltest du nicht nur die Zukunft unserer datengestützten Lösungen, sondern führst und entwickelst auch ein hochqualifiziertes Team von Data Scientists. Du bist die treibende Kraft hinter unserer Innovationsagenda und stellst sicher, dass wir durch datengetriebene Ansätze den maximalen Wert für unsere Kunden generieren und unsere Marktposition weiter ausbauen.

• Team Leadership & Entwicklung: Du führst, motivierst und entwickelst ein Team von Data Scientists und förderst eine kollaborative sowie leistungsstarke Teamkultur.
• Stakeholder Management & Beratung: Als zentraler Ansprechpartner für interne Fachbereiche sowie für Top-Kunden übersetzt du komplexe datenwissenschaftliche Erkenntnisse in klare, handlungsrelevante Empfehlungen.
• Projekt- & Portfolio-Management: Du überwachst das Projektportfolio deines Teams, stellst die Einhaltung von Zeitplänen sowie Budgets sicher und priorisierst Initiativen auf Basis ihres geschäftlichen Impacts.
• Innovation & Forschung: Aktiv beobachtest du Markttrends und wissenschaftliche Entwicklungen im Data-Science-Bereich und treibst den Transfer von Forschungsergebnissen in die Praxis voran.
• Qualitätssicherung & Governance: Die Etablierung und Überwachung von Qualitätsstandards für unsere Data-Science-Projekte gehören ebenso zu deinen Aufgaben wie die Sicherstellung der Einhaltung relevanter Daten-Governance-Richtlinien.
• Strategische Ausrichtung: Als treibende Kraft unserer Innovationsagenda stellst du sicher, dass wir durch datengetriebene Ansätze den maximalen Wert für unsere Kunden generieren und unsere Marktposition weiter ausbauen.

Das zeichnet dich aus:

• Umfassende Erfahrung: Du bringst mindestens 5+ Jahre Berufserfahrung im Bereich Data Science mit, davon mindestens 2-3 Jahre in einer leitenden Position mit Personalverantwortung.
• Exzellente Fachkenntnisse: Deine Expertise in Python (Pandas, Scikit-learn, TensorFlow/PyTorch), SQL sowie in der Entwicklung und Implementierung von Machine Learning Modellen ist fundiert und praktisch erprobt.
• Cloud-Expertise: Du verfügst über nachweisliche Erfahrung mit Cloud Computing Plattformen, idealerweise Google Cloud Platform (GCP), inklusive ML-Services und Data Warehousing (z.B. BigQuery).
• Führungskompetenz: Ausgeprägte Führungsqualitäten mit der Fähigkeit, Teams zu motivieren, zu coachen und zu Höchstleistungen zu entwickeln, zeichnen dich aus.
• Kommunikations- & Präsentationsstärke: Deine exzellenten Kommunikationsfähigkeiten ermöglichen dir sowohl die Präsentation komplexer Modelle vor technischen Teams als auch die strategische Beratung von Führungskräften und Kunden.
• Strategisches Denken & Geschäftssinn: Die Fähigkeit, komplexe geschäftliche Herausforderungen zu verstehen und datengetriebene Lösungen zu entwickeln, die einen messbaren Mehrwert schaffen, rundet dein Profil ab.

Darüber hinaus bist du: #selbständig #teamfähig #lösungsorientiert

Wenn du diesen Job spannend findest, dann ermutigen wir dich ausdrücklich zur Bewerbung, auch wenn du nicht jede oben gelistete Qualifikation aufweisen kannst.

Arbeiten bei WPP Media:

Als WPP Media gestalten wir die Zukunft der Medien und investieren dabei konsequent in unsere Mitarbeiter:innen. Jede:r Kolleg:in genießt die Vorteile des globalen Netzwerks von WPP Media und WPP, um sich weiterzuentwickeln und an der Spitze von Marketing und Werbung zu lernen. Vielfalt und Zusammenhalt leben wir durch zahlreiche Employee Resource Groups und regelmäßige interne Events - zum Austausch, zur Inspiration und zum gemeinsamen Feiern unserer Erfolge.
 
WPP Media ist ein Arbeitgeber, der Chancengleichheit fördert. Wir berücksichtigen alle Bewerber:innen für alle Positionen ohne Diskriminierung. Unser Ziel ist eine Kultur des Respekts und der Zugehörigkeit, in der jede:r die gleichen Möglichkeiten hat, sich einzubringen und beruflich zu wachsen.

Bitte lies unsere Datenschutzerklärung für Deutschland, Österreich und die Schweiz, um weitere Informationen darüber zu erhalten, wie wir die von dir bereitgestellten Daten verarbeiten. 

Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.

Who you are

We are looking for a highly motivated and analytical Data Scientist to join our growing data team. You will play a key role in extracting insights from large datasets, building predictive models, and supporting data-driven decision-making across departments.

What you'll do

• Collect, process, and analyze large datasets from multiple sources
• Build and deploy machine learning models to solve business problems
• Design and implement A/B tests and statistical analyses
• Collaborate with cross-functional teams (product, engineering, marketing) to define analytics requirements
• Communicate complex data insights in a clear and actionable manner to stakeholders
• Develop dashboards and visualizations to monitor key metrics
• Stay current with the latest trends and technologies in data science and AI

What we're looking for

• Bachelor’s and or Master’s degree in Computer Science, Mathematics, Statistics, or related field
• 4+ years of proven experience as a Data Scientist or Data Analyst
• Strong knowledge of Python/R and SQL
• Hands-on experience with machine learning frameworks (e.g., scikit learn, tensroflow, pytorch)
• Experience with big data tools (e.g., Spark, Hadoop)
• Familiarity with data visualization tools
• Strong analytical, problem-solving, and communication skills

While not required, these are a plus:

• Experience with cloud platforms preferably AWS (S3, Sagemaker, Airflow etc)
• Strong SQL skills, with experience in Snowflake, MySQL, and PostgreSQL
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker)

3 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. #LI-SR1 #LI-Onsite

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

Open to overseas candidates/Visa Support

This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.

The Impact You’ll Make at Appier

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.

In this role, you’ll further improve bidding strategies, audience targeting and creative optimization by deep-diving RTB ecosystem including SSP/DSP/MMP to design the strategy, enhancing user signals or applying advanced deep learning model

What You’ll Work On

• Deep-dive the RTB ecosystem to identify the potential direction and decide the bidding strategy
• Leverage advance deep learning model to improve bidding/audience model performance
• Co-work with teams to improve real-time/long-term user interaction signal collection and to further improve model performance

What We’re Looking For

• Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field.
• 3+ years of industry experience on RTB ecosystem
• Proficiency in Python and SQL experience with modern ML frameworks and deep learning model (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills.

#LI-AK1

Key Responsibilities:

• Lead the technical strategy and execution for SoundCloud’s ML systems (e.g., recommendation, ranking, personalization), including model development, deployment, and scaling
• Lead the exploration of advanced modeling techniques including Deep Neural Networks, LLMs, large recommender systems, multi-modal embeddings and transformer-based architectures to create unique and impactful listening experiences
• Define and drive the overall technical direction for ML in SoundCloud including model architecture, feature engineering, training and serving infrastructure at scale, feature stores, pipeline orchestration, and model registry and versioning all aimed at accelerating our ability to bring ML-powered features to market
• Own short- and long-term objectives, ensuring ML investments deliver measurable user and business impact
• Lead, mentor, and grow ML Engineers and Scientists across SoundCloud
• Be a strategic partner to the CTO in bringing an “ML Everywhere” strategy to all surfaces in the product (both Creator and Fan), and helping to lead the charge on AI-native engineering
• Stay current with industry trends and advancements in machine learning, identifying opportunities to apply them at SoundCloud
• Lead the leveraging of agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods

Experience and Background:

• 10+ years of experience in ML engineering, plus 3+ years in search or recommendations in an internet scale service with the reach of tens of millions of daily active users. Experience in a music streaming environment is a bonus
• Proven track record of defining technical strategy and driving execution for large-scale ML systems, particularly in recommendation, personalization, or search
• Experience setting technical roadmaps, influencing cross-functional priorities, and balancing business, product, and engineering trade-offs at an organizational level
• Experience leading and scaling teams of ML Engineers and Scientists, including hiring, mentoring, and developing high-performing talent
• Deep expertise in delivering data-driven products and ML solutions at scale on cloud-based platforms, with strong understanding of infrastructure and lifecycle management
• Hands-on familiarity with modern ML frameworks (PyTorch, TensorFlow) and data processing pipelines, combined with strong software engineering foundations
• Thought leadership in ML and data science, with a track record of driving technical innovation and applying emerging industry trends
• Exceptional communication, strategic influence, and cross-functional leadership skills across senior stakeholders and global teams

The salary range for this role is $280,000 - $325,000 annually. The final salary offered will be determined based on relative experience, skills, internal equity, and location. We also offer a generous total rewards program - read more about additional benefits and perks below!

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Comprehensive health benefits including medical, dental, and vision plans, as well as mental health resources
• Robust 401k program
• Employee Equity Plan
• Generous professional development allowance
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• 16 paid weeks for all parents (birthing and non-birthing), regardless of gender, to welcome newborns, adopted and foster children
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

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

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

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

Role Overview

As our Staff Machine Learning Engineer for Coupang Media Group, Ads Quality, you will be responsible for developing, designing machine learning models, optimization algorithms and new product features for our advertising platform. 

The Coupang Media Group (CMG) is responsible for providing vendors that sell their products on Coupang a host of marketing products and services.  We launched Product Ads performance advertising marketplace late in 2018.  We have grown rapidly to over 10,000 active advertisers and 150M daily ad impressions in only 5 months’ time. Our group is responsible for advertising brands and products inside our e-commerce website. To get an idea of how valuable that is, both Alibaba and Amazon make more money on advertising than on selling products.  

This is an opportunity to be part of building up a new development organization with strong revenue potential inside a successful company. We’re building full-stack engineering teams to handle large scale advertising problems, including real-time behavioral targeting, auctioning and bidding systems and search based advertising. 

We are in the growth phase of the organization, so you’ll be a part of managing the transition from growth phase to enterprise processes. 

In this role you will be responsible for innovating and building our new ad quality stack for our ads platform  and eventually extend it into a full ad exchange, DSP, and SSP. We currently handle about 1bn impressions per day from internal traffic alone. 

What You Will do

• Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement 
• Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning, and vector search
• Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning
• Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
• Define and track key performance metrics to evaluate model impact and identify high[1]leverage opportunities for improvement
• Collaborate cross-functionally with product, engineering, and data science teams to align technical solutions with business goals and customer experience
• Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
• 4 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML systems

Preferred Qualifications

• Master’s or PhD in relevant technical fields
• Experience with search systems, information retrieval or recommendation engines
• Experience with LLMs, embeddings, and vector search technologies
• Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
• Experience working in startup or high-growth environments
• Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
• Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit[1]learn, Keras, XGBoost, LightGMB, and H2o.ai
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work independently and manage ambiguity in fast-paced environments

General Description of All Benefits

• Annual bonus is 0-20% of the base salary
• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• 6 weeks Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

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

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate.

Recruitment Process and Others

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.

• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

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

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Requisition ID: R0072711

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

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

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

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

Role Overview

As our Staff Machine Learning Engineer for Coupang Media Group, Ads Quality, you will be responsible for developing, designing machine learning models, optimization algorithms and new product features for our advertising platform. 

The Coupang Media Group (CMG) is responsible for providing vendors that sell their products on Coupang a host of marketing products and services.  We launched Product Ads performance advertising marketplace late in 2018.  We have grown rapidly to over 10,000 active advertisers and 150M daily ad impressions in only 5 months’ time. Our group is responsible for advertising brands and products inside our e-commerce website. To get an idea of how valuable that is, both Alibaba and Amazon make more money on advertising than on selling products.  

This is an opportunity to be part of building up a new development organization with strong revenue potential inside a successful company. We’re building full-stack engineering teams to handle large scale advertising problems, including real-time behavioral targeting, auctioning and bidding systems and search based advertising. 

We are in the growth phase of the organization, so you’ll be a part of managing the transition from growth phase to enterprise processes. 

In this role you will be responsible for innovating and building our new ad quality stack for our ads platform  and eventually extend it into a full ad exchange, DSP, and SSP. We currently handle about 1bn impressions per day from internal traffic alone. 

What You Will do

• Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement 
• Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning, and vector search
• Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning
• Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
• Define and track key performance metrics to evaluate model impact and identify high[1]leverage opportunities for improvement
• Collaborate cross-functionally with product, engineering, and data science teams to align technical solutions with business goals and customer experience
• Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
• 4 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML systems

Preferred Qualifications

• Master’s or PhD in relevant technical fields
• Experience with search systems, information retrieval or recommendation engines
• Experience with LLMs, embeddings, and vector search technologies
• Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
• Experience working in startup or high-growth environments
• Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
• Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit[1]learn, Keras, XGBoost, LightGMB, and H2o.ai
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work independently and manage ambiguity in fast-paced environments

Pay & Benefits

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

The base pay for Staff position ranges from $152K/year to $261K/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits

• Annual bonus is 0-20% of the base salary
• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• 6 weeks Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

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

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate.

Recruitment Process and Others

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.

• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

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

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Requisition ID: R0072711

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

• Proactively drive the execution of end-to-end data platform, data quality roadmap for Search & Discovery ML efforts
• Take ownership, consolidate and optimize the Search & Discovery core data logging, processing, and ML model training pipelines
• Develop and scale data infrastructure that powers batch and real-time data processing, monitoring, and debugging for ML experiments
• Drive design and implementation of scalable ML based ranking system and online ML inference services
• Build strong cross-functional partnerships with Data Scientists, Analysts, Product Managers, Indexing Platform Engineers, Ranking Engineers and Data Platform Engineers to understand both the offline and online needs and deliver on those needs
• Research, analyze and select technical approaches for solving difficult and challenging development and integration problems, coach and mentor other engineers in process and methodologies

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or
  closely related fields
• 8 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML
  systems

Preferred Qualifications

• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning)
• Experience with Big Data tools and ETL frameworks (Hadoop, Hive, Presto, Spark, Scala, Apache Airflow, etc.)
• Experience with ML frameworks such as Tensorflow and Pytorch
• Experience with deploying highly robust and scalable data pipelines processing petabytes of data
• Experience in managing mission critical services with high throughput and low latency
• Experience with integrating applications and platforms with cloud technologies (i.e, AWS and GCP)
• Strong verbal and written communication skills
• Ability to conduct meetings and make professional presentations, and explain complex concepts and technical material to non-technical users
• Experience with machine learning platform for search & discovery related rankings is a strong plus

Pay & Benefits

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

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

General Description of All Benefits

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

General Description of Other Compensation

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

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

Details to Consider

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

Privacy Notice

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

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate. Coupang is also committed to providing a safe work environment for its employees and its consumers.

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Requisition ID: R0069890

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

• Proactively drive the execution of end-to-end data platform, data quality roadmap for Search & Discovery ML efforts
• Take ownership, consolidate and optimize the Search & Discovery core data logging, processing, and ML model training pipelines
• Develop and scale data infrastructure that powers batch and real-time data processing, monitoring, and debugging for ML experiments
• Drive design and implementation of scalable ML based ranking system and online ML inference services
• Build strong cross-functional partnerships with Data Scientists, Analysts, Product Managers, Indexing Platform Engineers, Ranking Engineers and Data Platform Engineers to understand both the offline and online needs and deliver on those needs
• Research, analyze and select technical approaches for solving difficult and challenging development and integration problems, coach and mentor other engineers in process and methodologies

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or 
  closely related fields
• 8 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML 
  systems

Preferred Qualifications

• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning)
• Experience with Big Data tools and ETL frameworks (Hadoop, Hive, Presto, Spark, Scala, Apache Airflow, etc.)
• Experience with ML frameworks such as Tensorflow and Pytorch
• Experience with deploying highly robust and scalable data pipelines processing petabytes of data
• Experience in managing mission critical services with high throughput and low latency
• Experience with integrating applications and platforms with cloud technologies (i.e, AWS and GCP)
• Strong verbal and written communication skills
• Ability to conduct meetings and make professional presentations, and explain complex concepts and technical material to non-technical users
• Experience with machine learning platform for search & discovery related rankings is a strong plus

Pay & Benefits

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

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

General Description of All Benefits

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

General Description of Other Compensation

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

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

Details to Consider

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

Privacy Notice

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

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate. Coupang is also committed to providing a safe work environment for its employees and its consumers.

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Requisition ID: R0069890

About the Team

The Counter Intrusion MSE team develops systems that provide force protection capabilities, monitoring the perimeter of secure areas, land or sea, for approaching people, vehicles, and vessels. We live in a world where security officers are increasingly overwhelmed by sensor data feeds. Our products leverage advanced sensor fusion and autonomy to seamlessly render activity in the environment to Lattice's common operating picture. This relieves operators of our system from a ton of burden and allows our customers to get more done with fewer personnel. Increasingly, Counter Intrusion MLEs are working on projects to bring customers' existing legacy security systems into the Lattice ecosystem. Key to this effort is building scalable software solutions so that we can service many customers without requiring bespoke software for each one. The Counter Intrusion team is responsible for the development, testing, deployment, and sustainment of our family of systems. We work closely with other teams from product, engineering, sales, logistics, operations, and mission success.

About the Role

We are looking for a Machine Learning Engineer to apply the latest research to solve our toughest problems. This role will be responsible for owning the whole machine learning stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for perception on edge compute devices that push the boundaries of what's possible with our sensors. You will develop learning algorithms to optimize the behavior of autonomous systems. You will also be responsible for the end-to-end design, implementation, and performance of the ML stack, including the infrastructure for data collection and training. Your work will directly impact Anduril's ability to deliver cutting-edge defense technology, with the opportunity to identify and develop novel ML applications across our product portfolio.

Responsibilities

• Propose and prototype innovative solutions to solve real-world problems, leveraging the latest state-of-the-art techniques in the field
• Develop and maintain core ML pipelines
• Train and deploy deep learning models for real-time applications
• Collaborate cross-functionally with camera, systems and labeling teams
• Curate datasets for evaluating performance and comparing performance trends over time
• Provide technical mentorship to other junior ML engineers

Required Qualifications

• MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision
• BS in Computer Science, Machine Learning, Electrical Engineering, or related field
• 6+ years of experience developing, benchmarking and optimizing ML algorithms on large-scale datasets
• Strong Deep Learning and CV background
• Proficiency in C++ development in a Linux environment
• Experience with Python development and deep learning frameworks such as PyTorch, JAX and TensorFlow
• Experience deploying models with TensorRT and ONNX
• Optimize on-device inference and vision kernels across CPU/GPU/NPU
• Track record of developing and deploying CV models from R&D to production
• Experience writing and maintaining automated continuous integration tests
• Knowledge of system profiling and tuning for latency, memory and power efficiency
• Ability to conduct experiments, ablation studies and create highly detailed reports
• Eligible to obtain and maintain a U.S. Secret security clearance

Preferred Qualifications

• Experience in one or more of the following:
• Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic Change Detection, Depth Estimation, Model Pruning and Compression
• Experience in one or more of the following:
• Visual Odometry, SLAM, Multi-view Geometry, Camera Models, RGB-D and LIDAR Sensor Fusion, Optical Flow
• Experience troubleshooting and analyzing remotely deployed software systems
• 1 year of experience in a technical leadership role

Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective.

You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. 

You Will:

Model and Pipeline Automation 

• Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. 
• Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
• Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.

Governance & Compliance

• Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.

Performance Monitoring

• Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. 
• Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.

Cross-Functional Collaboration

• Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
• Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.

Architecture and Infrastructure Management

• Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
• Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
• Distill complex ML concepts into easy-to-follow technical documentation.

You Have:

• 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines. 
• 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
• 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
• Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms. 
• Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
• Experience developing, documenting, and supporting REST APIs
• A degree in Computer Science, Engineering, or a related field or equivalent practical experience.

About the Role

At Together.ai, we are building state-of-the-art infrastructure to enable efficient and scalable inference for large language models (LLMs). Our mission is to optimize inference frameworks, algorithms, and infrastructure, pushing the boundaries of performance, scalability, and cost-efficiency.

We are seeking an Inference Frameworks and Optimization Engineer to design, develop, and optimize distributed inference engines that support multimodal and language models at scale. This role will focus on low-latency, high-throughput inference, GPU/accelerator optimizations, and software-hardware co-design, ensuring efficient large-scale deployment of LLMs and vision models.

This role offers a unique opportunity to shape the future of LLM inference infrastructure, ensuring scalable, high-performance AI deployment across a diverse range of applications. If you're passionate about pushing the boundaries of AI inference, we’d love to hear from you!

Responsibilities

Inference Framework Development and Optimization

• Design and develop fault-tolerant, high-concurrency distributed inference engine for text, image, and multimodal generation models.
• Implement and optimize distributed inference strategies, including Mixture of Experts (MoE) parallelism, tensor parallelism, pipeline parallelism for high-performance serving.
• Apply CUDA graph optimizations, TensorRT/TRT-LLM graph optimizations, and PyTorch-based compilation (torch.compile), and speculative decoding to enhance efficiency and scalability.

Software-Hardware Co-Design and AI Infrastructure

• Collaborate with hardware teams on performance bottleneck analysis, co-optimize inference performance for GPUs, TPUs, or custom accelerators.
• Work closely with AI researchers and infrastructure engineers to develop efficient model execution plans and optimize E2E model serving pipelines.

Requirements

Must-Have:

• Experience:
  • 3+ years of experience in deep learning inference frameworks, distributed systems, or high-performance computing.
• Technical Skills:
  • Familiar with at least one LLM inference frameworks (e.g., TensorRT-LLM, vLLM, SGLang, TGI(Text Generation Inference)).
  • Background knowledge and experience in at least one of the following: GPU programming (CUDA/Triton/TensorRT), compiler, model quantization, and GPU cluster scheduling.
  • Deep understanding of KV cache systems like Mooncake, PagedAttention, or custom in-house variants.
• Programming:
  • Proficient in Python and C++/CUDA for high-performance deep learning inference.
• Optimization Techniques:
  • Deep understanding of Transformer architectures and LLM/VLM/Diffusion model optimization.
  • Knowledge of inference optimization, such as workload scheduling, CUDA graph, compiled, efficient kernels
• Soft Skills:
  • Strong analytical problem-solving skills with a performance-driven mindset.
  • Excellent collaboration and communication skills across teams.

Nice-to-Have:

• Experience in developing software systems for large-scale data center networks with RDMA/RoCE
• Familiar with distributed filesystem(e.g., 3FS, HDFS, Ceph)
• Familiar with open source distributed scheduling/orchestration frameworks, such as Kubernetes (K8S)
• Contributions to open-source deep learning inference 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: $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

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

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 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 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.

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

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

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

Role Overview

What You Will do

• Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement
• Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning, and vector search
• Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning
• Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
• Define and track key performance metrics to evaluate model impact and identify high[1]leverage opportunities for improvement
• Collaborate cross-functionally with product, engineering, and data science teams to align technical solutions with business goals and customer experience
• Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
• 4 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML systems

Preferred Qualifications

• Master’s or PhD in relevant technical fields
• Experience with search systems, information retrieval or recommendation engines
• Experience with LLMs, embeddings, and vector search technologies
• Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
• Experience working in startup or high-growth environments
• Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
• Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit[1]learn, Keras, XGBoost, LightGMB, and H2o.ai
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work independently and manage ambiguity in fast-paced environments

Pay & Benefits

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

The base pay for Staff position ranges from $152K/year to $277K/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits

• Annual bonus is 0-20% of the base salary
• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• 6 weeks Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

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

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate.

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.

• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

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

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Req: R0069012

About the Role

We're hiring an AI Engineer to work on the AI core of Mill Commercial — the computer vision and agentic systems that turn a stream of food waste into operational intelligence for commercial kitchens. Mill Commercial integrates a camera and onboard compute directly into our high-capacity food recycler; models running on the edge identify, classify, and quantify food scraps at the point of generation, and our vision pipeline turns that signal into procurement and operational guidance for large food service operators.

You'll join a small AI team, building the data and training pipeline that produces our edge CV models, designing the cloud-side evaluation that tells us whether those models are good enough to ship, and helping build the agentic, LLM-driven product features that turn raw waste data into customer-facing insights and recommendations. This is a hands-on senior IC role for someone who's equally comfortable fine-tuning a segmentation model, prompting a VLM, and wiring an agent into a product feature.

What You'll Do

• Build and manage the end-to-end ML training pipeline: data ingestion from deployed kitchen units, ground truth generation, annotation tooling (including foundation-model-assisted labeling), training, evaluation, and retraining cycles.
• Train and evaluate segmentation, classification, and mass-estimation models for the Mill Commercial camera pipeline — from prompting foundation models to fine-tuning ConvNets and VLMs.
• Build the cloud-side evaluation harness that tells us how our shipped edge models are actually performing in the field — automated, reproducible, and aligned to product accuracy targets across food types, kitchen environments, and deployment configurations.
• Own MLOps: reproducible training, experiment tracking, model versioning, and automated evaluation against product-defined accuracy targets.
• Export and validate models for deployment to edge devices, working closely with the edge team on optimization, quantization, and integration.
• Help design and build the LLM- and agent-powered product features that consume waste characterization data and turn it into customer-facing recommendations — purchasing suggestions, anomaly explanations, operational nudges. Define how agents call tools, ground in customer data, and stay reliable in production.
• Analyze failure cases systematically — unfamiliar food classes, novel kitchen environments, challenging lighting and clutter conditions — and drive the data and modeling decisions that close accuracy gaps.

What We're Looking For

• Strong fundamentals in computer vision and deep learning — segmentation, detection, classification, tracking. You understand the architectures well enough to make informed choices.
• Fluency with modern ML approaches — VLMs, LLMs, foundation models, and agentic systems — alongside classical deep learning. You know when to fine-tune a ConvNet, when to prompt a VLM, and when to wire up an agent, and you understand the practical realities of putting any of them into a product.
• Experience building ML training pipelines and data annotation systems at scale.
• Experience evaluating ML models rigorously — designing metrics, building the eval harness, and using results to drive product decisions rather than just publish a number.
• Proficiency with cloud ML infrastructure (AWS or equivalent) — you've managed training jobs, data pipelines, and experiment workflows in production.
• Familiarity with cloud-to-edge model deployment.
• Clear, direct communication — you can explain tradeoffs to non-technical stakeholders, push back honestly when you disagree, and write docs that others can follow.
• Genuine interest in applying AI to food waste reduction and sustainability. This is a mission-driven product and we want people who care about the mission.

Software skills: Python, PyTorch, OpenCV. Strong familiarity with MLOps on AWS infrastructure. Experience with LLM and agent frameworks. Google Cloud / Gemini experience is a plus.

Nice to Have

• Experience with video understanding (temporal consistency, tracking, video segmentation)
• Experience with foundation models for data annotation
• Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, or equivalents)
• Experience shipping LLM- or agent-powered features in a consumer or B2B product
• Hardware / IoT product experience, particularly with computer vision and cameras for embedded systems

The estimated base salary range for this position is $240 to $280k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

• 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 we continue to expand our footprint, we are looking for a sharp, agile, and business-minded lawyer to join our lean legal team. You will be the primary engine behind our commercial contracting process. This is not a "siloed" role; you will be the cross-functional glue between Finance, Engineering, Sales, and Security, ensuring our legal strategy moves at the speed of our innovation. 

This is an ideal opportunity for a high-performing lawyer with a strong grasp of transactional fundamentals who is ready to "level up." While your primary focus will be owning the commercial contract lifecycle, you will have a front-row seat to the broader legal challenges of a hyper-growth AI company.

You will be joining the Legal Team and report to our VP of Legal. This is a hybrid role based in our San Francisco or New York office with an in-office requirement of 2 days per week.

What You’ll Do

• Lead the drafting and negotiation of a wide variety of contracts, including Master Service Agreements (MSAs), NDAs, Data Processing Addenda (DPAs), and vendor agreements.
• Serve as the legal point of contact for CX, Sales, Engineering, and Finance teams to streamline deal cycles and mitigate risk.
• Navigate complex technology transactions, specifically focusing on intellectual property rights and data privacy frameworks in the context of AI and cloud computing.
• Beyond commercial matters, you will assist the VP of Legal on special projects, potentially spanning corporate governance, employment, and regulatory compliance as the company scales.

What You’ll Need

• 3–5 years of legal practice, with a focus on commercial or corporate transactions.
• A proven track record at a top-tier law firm, in-house at a high-growth tech company, or a strategic mix of both.
• A deep understanding of technology transactions, including the nuances of IP licensing and data privacy provisions.
• You are a confident negotiator who knows when to hold the line and when to find a creative solution to get the deal done.

Compensation

What We’re Looking For

We are looking for a Senior Finance Associate to drive priorities across strategic finance, corporate development, and FP&A as Lightning AI scales. You will partner with cross-functional stakeholders to shape unit economics, advise on deal pricing, and guide investment decisions. You will support GPU financing, fundraising, and investor relations to help Lightning AI acquire and allocate capital effectively. You will also build an operating cadence for P&L management, reporting, forecasting, and planning, turning data into decision-ready insights for leadership. 

The finance scope is deep, leadership visibility is high, and the work directly influences revenue growth, margin expansion, and capital allocation. If you want meaningful ownership, steep learning, and proximity to the decisions that shape an AI cloud, this role is for you.

This is a hybrid role based in our San Francisco or New York office with an in-office requirement of 2 days per week.

What You’ll Do

• Support deal reviews with Sales and leadership and recommend pricing decisions
• Partner with Marketing on spend allocation, pipeline efficiency, and unit economics analyses (LTV/CAC, payback period)
• Partner with Product on ROI for software investments and strategic initiatives
• Partner with Infrastructure Operations on capacity planning and CapEx assessment
• Model GPU financing structures and assess returns
• Support lender and investor communications, materials, and data rooms
• Monitor industry trends and the competitive landscape to identify potential business risks and opportunities
• Contribute to M&A sourcing and diligence models
• Build and maintain a driver based model for P&L, balance sheet, and cash flow statement
• Prepare executive-level business reviews for leadership and board
• Lead monthly and quarterly reporting, ensuring accuracy and highlighting key business drivers
• Develop forecast cycles and strengthen forecast accuracy by partnering closely with cross-functional stakeholders
• Support annual planning and long-range planning 
• Conduct rigorous analysis of key performance indicators, operational metrics, and business trends
• Manage FP&A systems and tooling and maintain data accuracy

What You’ll Need

• Bachelor's degree in Business Administration, Finance, Economics, or a related field
• 4+ years in Strategic Finance, FP&A, investment banking, private equity, or venture capital, ideally with a focus on software, AI, and/or cloud infrastructure
• Advanced proficiency in Excel and Google Sheets and experience building complex financial models
• Excellent written and verbal communication
• Track record of cross-functional partnership
• Analytical and strong problem-solving ability
• Team player with a growth mindset, positive attitude, and strong work ethic
• Bias to action and desire to work in a startup environment
• Experience with capital markets, M&A, or CapEx financing
• Exposure to cloud or AI infrastructure economics and data center capacity planning
• Familiarity with FP&A systems and data tooling (e.g., NetSuite)

Compensation

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 an Observability Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own and evolve observability systems across large-scale, GPU-enabled bare-metal infrastructure. You’ll operate at the intersection of infrastructure, data, and product, building platforms for metrics, logs, traces, and alerting that power both internal operations and customer-facing visibility.

You will play a key role in productizing observability, enabling scalable, multi-tenant monitoring experiences while keeping pace with rapid infrastructure buildouts. This includes designing telemetry pipelines, improving signal quality, and delivering actionable insights that ensure reliability and transparency across our platform.

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

Observability Platform & Productization

• Own and evolve a scalable observability platform spanning metrics, logs, traces, and events
• Drive the productization of observability capabilities for both internal teams and external customers
• Design multi-tenant observability systems with scoped access, RBAC, and customer-facing visibility
• Continuously improve observability systems to keep pace with rapid infrastructure buildouts

Telemetry & Data Pipelines

• Design and operate telemetry pipelines ingesting data from GPUs, CPUs, networking (Ethernet & InfiniBand), containers, APIs, and BMC/Redfish
• Build systems to correlate signals across infrastructure layers to enable faster debugging and root cause analysis
• Implement streaming and real-time data pipelines using tools such as Kafka, OTEL, Promtail, or similar

Alerting, Reliability & Insights

• Design and implement noise-resistant alerting systems to improve signal quality and reduce operational load
• Create dashboards and alerting for InfraOps, Engineering, and Customer Success teams
• Build automated insights and enable proactive detection, forecasting, and system health visibility at scale

Systems & Infrastructure Engineering

• Contribute to broader infrastructure engineering projects beyond observability
• Partner with infrastructure and platform teams to embed observability into core systems and workflows
• Support large-scale, distributed systems across compute, networking, and storage environments

Cross-Functional Collaboration

• Work closely with customer-facing teams to deliver external observability experiences
• Collaborate with engineering, operations, and support teams to improve system transparency and reliability
• Help define best practices for observability across the organization

What You’ll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, SRE, or observability-focused roles
• Strong experience with monitoring systems such as Prometheus, Grafana, ELK, or VictoriaMetrics
• Experience building and operating observability platforms at scale
• Proficiency in Python, Go, or bash for automation and data integration
• Familiarity with containerized environments and Kubernetes observability
• Experience with streaming telemetry pipelines (Kafka, OTEL, Promtail, or equivalent)
• Experience with multi-tenant monitoring architectures
• Strong written and verbal communication skills

Ideal Experience

• Experience with GPU observability, particularly NVIDIA DCGM
• Experience monitoring large-scale GPU or HPC clusters
• Familiarity with InfiniBand fabric observability
• Experience building customer-facing or productized infrastructure systems
• Experience with correlation engines, RCA workflows, or predictive alerting systems
• Broad exposure to infrastructure domains including networking, storage, and provisioning

Compensation

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

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 Frontend Engineer to help develop and scale the UI and frontend infrastructure of the Lightning AI platform. 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. With over 10,000 organizations building with Lightning, you’ll have a unique opportunity to impact how the world builds and deploys AI to production.

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 React and Redux, and 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 user interface and frontend infrastructure 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 in which each engineer can grow.

What You’ll Need

• Proficiency in React, JavaScript and TypeScript.
• Strong understanding of software engineering principles and lifecycle.
• Hands-on experience as a Frontend 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

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 AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!

Location:  Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

What You’ll Do

• Develop and maintain highly interactive, large-scale and complex web-based visual analytics tools on AI/ML workloads.
• Design and implement creative and performant visualizations to assist in diagnosing issues or uncovering optimization opportunities in AI/ML inference and serving.
• Collaborate closely with hardware architects and compiler engineers to define, design, and implement effective visualization solutions enhancing their workflow.
• Develop high-performance visualization workflows by integrating independent graphics modules with micro-services to handle asset optimization, ensuring a non-blocking experience on the client.
• Continuously seek improvements to existing tools and develop new approaches to meet fast-evolving requirements.
• Stay up-to-date with the latest advancements in web development and visualization techniques.
• Contribute to the development of the documentation and user guides.
• Complete other responsibilities as assigned.

What You Bring

• Bachelor’s with 10+ years, or Master’s with 8+ years, or PhD's with 5+ years of industry experience.
• An innate drive to clarify deep technical complexity, balancing creative visualization with engineering rigor to build analytical tools that make interdependent hardware and software models intuitive without sacrificing logical precision.
• Strong experience in full-stack visual analytics software development, with a focus on building scientific or infrastructure visualization tools. Experience in AI model visualization integrated with PyTorch is a plus.

• Strong proficiency in modern frontend technologies like React and backend technologies like Node.js or Python-based frameworks. Experience in graph-based UI is a plus.
• Proven experience in WebGL/WebGPU based frameworks such as three.js or deck.gl. GLSL experience is a plus. Experience in WebAssembly with C++ is a plus.
• Excellent problem-solving skills and ability to think critically and creatively.

• Excellent communication and interpersonal skills.
• Ability to work independently and as part of a team.
• You’re inclusive, adapting your style to the situation and diverse global norms of our people.
• An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.
• Innovative and creative, you proactively explore new ideas and adapt quickly to change.

#LI-VL1

Cherchez-vous à vous épanouir dans un environnement de travail stimulant? 

Joignez-vous à Levio, un leader de la transformation numérique, et propulsez votre carrière vers de nouveaux sommets. Vous travaillerez aux côtés de professionnels de haut calibre sur des projets technologiques ambitieux et de grande envergure, directement intégrés dans les environnements de nos clients. Chez Levio, nous valorisons l’expertise, la curiosité et l’amélioration continue  et nous vous offrons l’espace nécessaire pour évoluer.

À propos du rôle 

Nous sommes à la recherche d'un Conseiller ML/IA pour concevoir, développer, déployer et exploiter des systèmes d’apprentissage automatique et d’IA générative de niveau production. Ce rôle couvre l’ensemble du cycle de vie des solutions ML, en veillant à ce que les modèles et services d’IA soient scalables, fiables, sécurisés et qu’ils génèrent une valeur d’affaires mesurable.

Pourquoi rejoindre Levio? 

• Travailler sur des projets de transformation numérique complexes et à fort impact
• Collaborer avec des équipes multidisciplinaires expérimentées
• Développer continuellement votre expertise technique et professionnelle
• Profiter de flexibilité, d’autonomie et d’une culture axée sur l’humain
• Faire partie d’une organisation qui valorise la diversité, l’inclusion et l’innovation

Rôle et responsabilités 

Summer Internship – IT & Data Analytics Intern (AI/ML Focus) 

Location:                      Irving, TX (On-Site) 
Department:                 Meriton IT & Data Analytics 
Internship Type:          Summer Internship (Full‑Time) 
Reports To:                  Hiring Manager – Meriton Technology & Analytics 

 If you’re looking to make an impact, we’re glad you’re here. At Meriton, you’ll join a team that believes in big ideas, doing great work, and building careers that matter—every step of the way. 

About the Role 

Meriton is seeking a highly motivated IT & Data Analytics Intern with a strong interest in Artificial Intelligence, Machine Learning, and Data Science. This role is ideal for students who enjoy problem‑solving, exploring emerging technologies, and applying analytics to drive insights and operational excellence. 

You’ll work closely with the Meriton technology team to support internal analytics, automation projects, and AI‑driven initiatives that enhance business decision‑making and improve efficiency. 

Key Responsibilities 

AI & Data Analytics 

• Assist in building and evaluating machine learning models, including data preprocessing, feature engineering, and model validation. 

• Use tools such as Cursor, Claude Code, AI Foundry, and similar AI development platforms to prototype automation and analytics solutions. 

• Conduct exploratory data analysis (EDA) on structured and unstructured datasets. 

• Support the creation of dashboards, reports, and visualizations for business stakeholders. 

• Research and recommend AI use cases that align with team strategy and business needs. 

IT & Technical Support 

• Collaborate with IT partners to streamline workflows through scripts, automation, and analytics. 

• Troubleshoot data, system, or integration issues as needed. 

• Document technical processes, workflows, and best practices. 

AI Product & Tooling Initiatives 

• Experiment with generative AI tools to assist with:  

• Query generation 

• Code generation & refactoring 

• Data pipeline development 

• Business insights summarization 

• Workflow automation 

• Partner with team members to test, evaluate, and implement AI‑powered solutions. 

Required Qualifications 

• Currently pursuing a degree in Computer Science, Data Science, Information Systems, Statistics, Engineering, or related fields. 

• Foundational coursework or hands‑on experience in:  

• Artificial Intelligence / Machine Learning 

• Data Science methodologies 

• Python, R, SQL, or similar languages 

• Comfortable working with modern AI coding tools such as:  

• Cursor (AI coding environment) 

• Claude Code / Claude AI 

• AI Foundry or other LLM ops platforms 

• Strong analytical thinking, problem‑solving abilities, and attention to detail. 

• Eagerness to learn, experiment, and adopt emerging technologies. 

Preferred Qualifications 

• Experience with:  

• Jupyter Notebooks 

• Pandas, NumPy, Scikit‑Learn, PyTorch or TensorFlow 

• Git / version control 

• Power BI or Tableau 

• Familiarity with API calls, cloud platforms, or DevOps automation. 

• Prior hands‑on project work involving AI agents, ML modeling, or generative AI use cases. 

Meriton is an equal opportunity employer

Machine Learning Engineer – Inspire11

Elevens, as we call ourselves here, are curiously smart, purposefully scrappy, and dedicated to the highest standard of quality. By being true to ourselves and others, we create a respectful environment that enhances collaboration, drives growth through high expectations, and ensures alignment with our core values. Inspire11 is more than a modern business and technology consulting firm; we're a revolution. We work differently — and it shows. Every move we make is tied to measurable value, and our success aligns with our clients’ success. We partner to simplify the complex, solve sustainably, and stay ahead by continuously pushing our own thinking forward. Value creation isn't something we talk about — it's something we live, every day. 

At Inspire11, we're not just offering a job; we're providing a platform for you to transform the future. You'll feel right at home here if you think differently, build boldly, and lead with impact. We're a place where your unique perspective is valued, your boldness is celebrated, and your potential is unleashed. 

• Growth Through Challenge:  We hold ourselves to the highest standards of excellence and accountability. At Inspire11, we are committed to delivering exceptional results and empowering our employees to take ownership of their work and drive meaningful impact. You'll work alongside elite consultants who challenge you to expand your skills and think even more creatively. 

• The Autonomy to Do Your Best Work: Here, outcomes matter more than outputs. It's about the value we create. You'll have the autonomy to shape your work, drive decisions, and make an impact—not just for our clients but for your growth. You'll be challenged to think strategically, anticipate needs, and solve problems. Bold thinking, creative approaches, and challenging conventional wisdom are part of our DNA. Our clients rely on us to lead them into what's next. 

• Diverse Perspectives Driving Innovative Solutions: We champion inclusivity and authenticity, knowing that diverse perspectives drive better solutions. You'll be encouraged to bring your whole self to work, knowing that's where true innovation happens. We also believe that doing great work should be fun. Our culture thrives on energy, camaraderie, and appreciating the unique contributions that make Inspire11 an amazing place. Our teams get energy from being the best they can be. 

 What you can expect in this role: 

• Designing scalable machine learning infrastructure, including implementing CI/CD pipelines for model deployment
• Monitoring models in production
• Developing Generative AI solutions
• Ensuring security and compliance
• Preprocessing and analyzing datasets
• Developing and fine-tuning ML models to optimize for performance
• Communicating results to stakeholders 

Tools for success: 

• Exhibit strong software engineering principles
• Proficiency in cloud architecture (AWS, Azure, GCP)
• Familiarity with CI/CD and DevOps
• Expertise in data preprocessing and ML techniques
• Experience with model evaluation and libraries like TensorFlow, PyTorch
• Proven experience in ML engineering
• Strong programming skills (Python, R)
• Cloud services and infrastructure knowledge
• Agile methodologies understanding 

Inspire11 is unable to sponsor employment visas at this time. Applicants must be legally authorized to work in the U.S. at the time of application and throughout the duration of employment. 

Inspire11’s Privacy Policy: https://www.inspire11.com/privacy-policy/  

U.S. Compensation & Benefits  

Compensation at Inspire11 
Inspire11 follows Title VII of the Civil Rights Act of 1964, the Equal Pay Act of 1963, the Illinois Human Rights Act, the Illinois Equal Wage Act, and the Illinois Equal Pay Act of 2003. We believe that people performing the same role at the same level, with similar levels of ability or experience, should be similarly compensated. We also believe that the most critical factors driving compensation should be an Eleven’s skill, experience, performance, responsibility, and effort. We may also consider an employee’s length of service, relevant education, training, or certification, and the requirements of a specific job. We may also consider whether the cost of living or competition for talent in specific markets requires adjustments in compensation for employees in those markets. Our goal is to fairly compensate all our Elevens based on these factors within the Company’s financial ability.   

Compensation may be increased or decreased at Inspire11’s discretion based on an employee’s performance reviews, market conditions, and the Company’s financial performance. Inspire11 will always notify an employee in writing before any change is made to their compensation.  

Bonuses 
We may allow employees in Sales, Recruiting, or Leadership to earn periodic bonuses based on sales, revenue, client-specific or practice-specific targets. These targets are communicated to each eligible employee via offer letter or annual update. All such target-based bonuses are calculated based on the Company and an individual’s periodic performance and will only be awarded if: (a) the employee is meeting performance expectations and is an employee in good standing of the Company; (b) the target is met; and (c) the Company’s current financial performance and market conditions permit the bonus to be paid out. All periodic bonuses are discretionary and are earned only when paid out.   

Each year, the Company will decide whether the Company’s financial performance, market performance, and business realities allow it to create an annual bonus pool. If the Company decides that annual bonuses may be awarded, then the Leadership Team will grant annual bonuses to employees in good standing based on the same factors discussed in the previous paragraph while also considering employees’ diligence, performance, expertise, skill, judgment, and experience. To be eligible to participate in this annual bonus pool, an employee must be hired by no later than October 1st of the preceding year. Annual bonuses and merit increases may be prorated based on hire date. Employees eligible for target-based periodic bonuses are not eligible to participate in the annual bonus pool.   

Options or Other Equity in Inspire11 
Inspire11 has a legacy program that allowed certain high-performing employees to purchase shares of the Company through an affiliate. The Company also has a newer program that grants options annually to high-performing employees based on their performance reviews, their managers’ recommendation, and leadership approval. These options have a vesting period associated with them.  

Benefits 
Full-time employees are eligible for the following contributory benefits, where premiums are partially paid by the Company and partially by the employee:   

• Medical insurance plans, 
• Dental insurance plans, and  
• Vision insurance plans.  

Full-time employees are eligible for the following benefits provided wholly by the Company:  

• Short-term disability, providing for a benefit of 60% of an employee’s salary up to a maximum of $2,000 per week for up to 11 weeks after a 7-day waiting period; 
• Long-term disability, providing for 60% of an employee’s salary up to a maximum of $10,000 per month for the time period from the 91st day after a qualifying event through the earlier of the end of the disability or age 67; 
• Life insurance, providing for a benefit of two times the employee’s annual salary, up to a maximum payout of $400,000;   
• A connectivity stipend of $325 annually; 
• Employee Assistance Program, providing for confidential counseling sessions, 24-hour crisis support, online peer support groups, skills training, behavioral health coaching, initial free legal consultations (and discounted rates on referred lawyers), online legal forms, assistance with eldercare and parenting services, among other things.  

Full-time employees are also eligible to participate in the Company’s 401(k) plan, which allows employees to contribute to a standard or Roth IRA. According to a vesting schedule, the Company matches 100% of employee contributions up to 3% of an employee’s salary.  

Depending on eligibility and their elections, full-time employees may also have access to certain tax-advantaged savings accounts set up through the Company, into which employees contribute withheld funds:   

• Flexible savings accounts
• Limited-purpose flexible savings accounts  
• Healthcare savings accounts
• Dependent care savings accounts  
• Commuter benefit accounts  

Paid Time Off and Leave 
Inspire11 grants all eligible employees any statutory leave required by federal, Illinois, or other applicable law, such as FMLA, bereavement, sick leave, emergency leave, jury duty or witness leave, and VESSA leave.   

In addition, Inspire11 has a self-managed paid time off policy (PTO) that does not set predetermined upper limits on the amount of PTO an employee may take. All PTO must be requested in advance and approved by the appropriate supervisor to ensure client work can continue. All full-time employees are expected to take a minimum of one week of PTO each year.   

Inspire11 offers paid parental leave to full-time employees who have been with the company for at least one year. Birthing parents are eligible for up to 12 weeks of paid parental leave, while non-birthing parents are eligible for up to 6 weeks. Short-term disability (STD) benefits are also provided following childbirth. When combined with PTO and STD, birthing parents may receive a total of 18–20 weeks of paid leave. Lastly, Inspire11 has eight paid holidays.  

Other Benefits 
Inspire11 also maintains other programs that provide additional benefits to employees, such as:   

• Impact to 11: a charitable giving matching program where, after being employed by Inspire11 for a year, employees may request that a qualifying charity receive up to $500 in matching donations each year. 
• Professional development benefits for qualifying employees: a program allowing for reimbursement of certain course materials and costs on a discretionary basis for employees who have been at Inspire11 for at least 6 months, with supervisor’s approval. 
• Regular gifts of Inspire11 clothes, office items, and swag.  

Disclaimer 
This document applies only to the United States and to Inspire11 LLC, not our worldwide partners.  

Inspire11 reserves the right to change the benefits offered to employees in accordance with applicable law based on business needs, market conditions, and financial stability. Before changing any benefits, Company will notify all employees of the change and will update this document.  

EEOC 
Inspire11 is an Equal Opportunity Workplace and an Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. If you need assistance or a reasonable accommodation during the application process, please contact us at hr@inspire11.com, or inform your recruiting partner.  

Riot engineers bring deep knowledge of specific technical areas but also value the opportunity to work in a variety of broader domains.  We work with both new and current technology, creating innovative solutions to solve complex, large-scale challenges and deliver player value.  As a Principal Software Engineer, you’ll lead the development of key features and model high standards of engineering excellence. 

As a Principal Software Engineer on Riot’s AI Enablement team, you are a technical force multiplier. You will embed directly with any team at Riot to accelerate their adoption of modern AI development (e.g., generative AI, LLMs, reinforcement learning). Operating as part of an elite, highly mobile strike team, you will build production-ready AI integrations, develop robust developer tools, and level up partner engineers through side-by-side collaboration. Once a team is empowered and systems are successfully handed off, you will deploy to the next challenge. You will be at the forefront of cutting-edge AI in the game industry, bridging the gap between new technologies and live environments to shape how Riot develops products and games. You will be accountable to Riot’s Head of AI Product.

Responsibilities:

• Implement and Integrate: Lead the technical execution of integrating modern AI practices into existing engines, tools, and pipelines.
• Embed and Accelerate: Deploy onto partner teams across Riot to break down complex AI implementation problems, establish technical direction, and deliver scalable, highly performant solutions.
• Mentorship and Handoff: Train and coach embedded team engineers through pair programming, technical reviews, and hands-on collaboration. Ensure a seamless transition of code ownership before deploying to your next assignment.
• Evangelize Best Practices: Share engineering best practices, security guardrails, and performance standards for AI usage across Riot’s development ecosystem.
• Build Foundations: Identify when industry-standard tools are insufficient and develop new foundations, middleware, or APIs to connect AI research with practical development.
• Manage Ambiguity: Actively navigate highly complex, uncharted technical spaces, communicating trade-offs and building consensus among engineering and product leadership.

Required Qualifications:

• BS in Computer Science (or equivalent experience) with 8-12 years of software engineering experience.
• Extensive experience with systems integration, technical leadership, and early-stage software development.
• Deep programming proficiency in C++ and at least one other language (e.g., Python, C#).
• Shipped at least one AAA game or large-scale, high-concurrency live service product.
• Proven track record of managing high ambiguity, setting technical strategy, and leading multi-month/year initiatives.
• Practical experience utilizing, integrating, or building modern AI tools, APIs, or infrastructure.

Desired Qualifications:

• Experience extending or developing within Unreal Engine (C++).
• Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) or LLM orchestration.
• Background working on shared engine technology, central tools, or platform engineering teams.
• Familiarity with the Runeterra and VALORANT IPs.

For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!

Our Perks:

Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information.

At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.

It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.

Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:

• Safeguarding confidential and sensitive Company data
• Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
• Accessing Company assets, secure digital systems, and networks
• Ensuring a safe interactive environment for players and other Rioters

These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. 

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.)

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a researcher at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this exciting field. As such, we’re looking for candidates who are keen scientists and engineers, with the theoretical and practical skills needed for impactful AI research.

We are looking for researchers with experience of AI in low-power, edge and embodied scenarios such as robotics, autonomous driving and augmented/virtual reality. We are interested in the training and deployment of multimodal AI models in these contexts, covering areas such as world models, real-time computer vision, generating and reasoning over audio/video streams.

The Team

Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences (NeurIPS, ICML, ICLR) as well as specialist workshops, and collaborate with other research teams and organisations across the world.

We pride ourselves on being a supportive and collaborative team, where we organise around our individual research interests to solve problems together in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications, including for sequence- and graph-based data. We’re based across London, Cambridge and Bristol, with projects and discussions that involve all our locations.

Perhaps the best way to get an idea of what we’re all about is to read one of our papers or an article on our blog. If you’re excited to work at the cutting edge of AI supported by new hardware and want to develop your skills in this area, we’d love to hear from you!

Responsibilities and Duties

• Generate AI/ML ideas, design experiments, implement them & evaluate results.
• Prepare, submit & present your work to AI conferences and workshops.
• Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.

About you:

Essential:

• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
• Experience in embodied AI, world models or robotics.
• Python programming in a modern deep learning framework, e.g. PyTorch or JAX.
• Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
• Capable of designing, executing and reporting from ML experiments.
• Mathematics skills to support the above: calculus, probability theory and linear algebra.
• Experience submitting papers to international scientific conferences or workshops.

Desirable:

• Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton.
• Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling.
• Practical familiarity with software stacks for deep learning – compilation, kernel fusion, XLA/ATen ops, streams, and asynchronous execution.
• Conference or workshop submissions in the fields of embodied AI, world models, or robotics.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

Snapshot 

At Google DeepMind, our research team is dedicated to tackling the most complex challenges in online information quality. We strive to advance the state of the art by developing innovative solutions to detect manipulated media and misleading narratives, ensuring the integrity of digital discourse. A prominent example of our scientific discovery is Backstory. Our interdisciplinary work spans provenance analysis and the creation of tools for AI-assisted information literacy, leveraging our technologies for the widespread public benefit of a safer online environment. We thrive in a supportive environment that encourages rapid prototyping and iteration, driving our research achievements directly into Google’s flagship models, including Gemini.

About us 

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. 

We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

The role

To succeed in this role, you will need to be passionate about advancing information literacy using machine learning and other computational techniques. You'll join an interdisciplinary team of domain experts, ML researchers, and engineers to research and build multimodal reasoning systems and Vision-Language Models (VLMs) to assess the trustworthiness of media (images, audio, and videos) on the internet.   

Key responsibilities:

• Plan and perform rapid prototyping of computer vision and multimodal machine learning techniques applied to determining authenticity of media information.
• Design and train multimodal models capable of complex visual reasoning.
• Undertake exploratory analysis to inform experimentation and research directions.
• Engage with product teams to drive the development of our research.
• Implement tools, libraries, and frameworks to speed up and enable new research.
• Report and present research findings, software developments, experimental results, and data analysis clearly and efficiently.
• Collaborate with internal and external scientific domain experts.

About you

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• PhD/Master’s degree in Computer Science, AI, ML, or equivalent practical experience.
• At least 2 years of relevant experience developing computer vision techniques or multimodal machine learning models.
• Experience in software development using Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a proven track record of building high-quality research prototypes and systems.
• Quantitative skills in math and statistics.
• Experience exploring, analysing and visualising data.

In addition, the following would be an advantage: 

• Experience in training and deployment of large-scale models.
• Experience with Video Understanding
• Experience with Large Language Models, prompt engineering, few-shot learning, post-training techniques, and evaluations.
• A proven track record of research or engineering achievements, such as publications in peer-reviewed conferences or journals.

When assessing technical background we will take a holistic view of the mix of scientific, ML and computational experience. We do not expect you to be an expert in all fields simultaneously.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

The US base salary range for this full-time position is between 174,000 USD - 252,000 USD + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

The Data Platforms Health team builds native platform solutions that enable healthcare-specific platform capabilities. This development role in the Database Platforms department will contribute to AI-based features and workflows within the InterSystems Health Connect Cloud, InterSystems FHIR Server, InterSystems IRIS for Health and InterSystems Health Connect products.

The team needs a developer who can drive AI model and AI architecture design and development for intelligent tooling features for healthcare builders and administrators. The team also needs thought leadership to adopt evolving AI technologies so that InterSystems can be a leader in AI-driven features and workflows.

You are encouraged to apply if this role sounds interesting to you, even if you have doubts about being a competitive candidate. InterSystems prides itself on investing in its team members.

This position is in the InterSystems headquarters in Boston, MA.

Responsibilities

You will design, build, train, and deploy machine learning and agentic AI models, and consume LLMs and custom models using REST APIs. Working with product management and support specialists, you will design and implement data cleansing and feature extraction tools to improve the accuracy of predictions and data generation for a healthcare setting. Your responsibilities will include integrating the models into existing products and refining the models to meet evolving product needs.

All work must follow the team’s development workflow including use of source control, design and code reviews, and clear documentation. You are responsible for the quality of your code and must design automated tests to verify the effectiveness of the models and features.

This role will require you to respond to technical questions about expected product behavior and recommended best practices from support specialists and sales engineers. You will also collaborate with the release engineering team to ensure that your model and tools are appropriately deployed in cloud and on-prem environments.

The technology stack includes Python, AWS Bedrock, ObjectScript, and InterSystems IRIS.

As a leader, you are expected to create project plans with estimates, track execution against the plan, and proactively communicate anticipated delays in the project. With support from your manager, you will coordinate with other teams and overcome blockers and inter-team misalignments to deliver your projects. You will also provide thought leadership in the areas of Gen AI, agentic AI, and other evolving technologies, and encourage other team members to adopt these technologies for the platform.

Qualifications Required

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
• 8+ years of hands-on professional experience as a software developer or similar. Open to considering less experience in combination with a Graduate degree.
• Experience with data analysis, data cleansing, feature extraction, and model training.
• Experience with Python and common libraries like Pandas, NumPy, and Scikit-learn.
• Experience with model training and evaluation.
• Experience with Agent orchestration and runtime, MCP, tool registration, and multi-model routing.
• Experience with design or consumption of REST APIs.
• Strong verbal and written communication skills.

Preferred Qualifications

• Self-starter with curiosity to experiment and learn, and confidence to challenge the status quo.
• Professional experience with machine learning algorithms like neural networks and LLMs.
• Professional experience with programmatic access of LLMs and/or open-source models.
• Experience with observability of model performance and runtime costs.
• Experience with model governance and design of guardrails for model security.
• Professional experience with deep learning libraries like TensorFlow, PyTorch, or Keras.
• Professional experience with health messaging standards, especially FHIR.
• 3+ years of experience with other programming languages like Java, C#, C++, or ObjectScript.

We are an equal-opportunity employer and do not discriminate because of race, color, religion, sex, national origin, ancestry, marital status, veteran status, age, disability, sexual orientation or gender identity or expression or any other legally protected category. InterSystems is an E-Verify Employer in the United States.

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

About the role:

We are looking for a motivated Data Science Intern to join our team. This role offers hands-on experience working with real-world data, building models, and supporting data-driven decision-making. You will collaborate with data scientists, engineers, and business stakeholders to solve meaningful problems.

What You'll Do :

• Collect, clean, and preprocess structured and unstructured data
• Perform exploratory data analysis to identify trends and insights
• Build and evaluate machine learning models under guidance
• Develop data visualizations and dashboards to communicate findings
• Assist in deploying models and monitoring their performance
• Work with large datasets using tools like Python, SQL, and cloud platforms
• Document processes, experiments, and results clearly
• Participate in team demos, feedback sessions, and learning opportunities.
• This role provides mentorship and exposure to customer-facing technical problem solving in a fast-moving AI/Product environment.

What We're Looking For:

• Enrolled in a Bachelor’s or Master’s degree program in Computer Science, Engineering, or a related field.
• Experience writing code in Python (or another general-purpose language).
• Strong interest in artificial intelligence, machine learning, or software engineering.
• Basic understanding of statistics and machine learning concepts
• Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow/PyTorch
• Experience with SQL and working with databases
• Strong analytical and problem-solving skills
• Excellent communication skills and willingness to collaborate with teammates and customers.

Nice-to-Haves

• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Knowledge of version control (Git)
• Exposure to big data tools (Spark, Hadoop) is a plus

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.com.