ml infrastructure engineer

Youtube

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>8 years of experience in software development.
</li><li>5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 
</li>
<li>5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 
</li>
<li>5 years of experience testing, and launching software products.</li>
<li>3 years of experience with software design and architecture.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field. 
</li>
<li>8 years of experience with data structures/algorithms.</li>
<li>3 years of experience in a technical leadership role leading project teams and setting technical direction. 
</li>
<li>3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. 
</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun &mdash; and we do it all together.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Design, develop, test, deploy, maintain, and enhance large scale software solutions. 
</li>
<li>Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables. 
</li>
<li>Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers. 
</li>
<li>Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies. 
</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Staff Software Engineer, AI/ML, YouTube

OpenAI

<div>
 
 About The Team
 
 
 
 OpenAI&rsquo;s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI&rsquo;s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.
 
 
 
 About The Role
 
 
 
 As a software engineer on the Scaling team, you&rsquo;ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI&rsquo;s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads.
 
 
 You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet.
 
 
 This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads.
 </li>
 <li>
 Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware.
 </li>
 <li>
 Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments.
 </li>
 <li>
 Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales.
 </li>
 <li>
 Develop simulation infrastructure to validate runtime behaviors, test training stack changes, and support early-stage hardware and system development.
 </li>
 <li>
 Rapidly deploy runtime and compiler updates to new supercomputing builds in close collaboration with hardware and research teams.
 </li>
 <li>
 Work across a diverse stack, primarily using Rust and Python, with opportunities to influence architecture decisions across the training framework.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You
 
 
 
 <ul>
 <li>
 Have a deep curiosity for how large-scale systems work and enjoy making them faster, simpler, and more reliable.
 </li>
 <li>
 Are proficient in systems programming (e.g., Rust, C++) and scripting languages like Python.
 </li>
 <li>
 Have experience in one or more of the following areas: compiler development, kernel authoring, accelerator programming, runtime systems, distributed systems, or high-performance simulation.
 </li>
 <li>
 Are excited to work in a fast-paced, highly collaborative environment with evolving hardware and ML system demands.
 </li>
 <li>
 Value engineering excellence, technical leadership, and thoughtful system design.
 
 
 </li>
 </ul>
 
 About OpenAI
 
 
 
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
 
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
 
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
 
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 
 
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 
 
 OpenAI Global Applicant Privacy Policy
 
 
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
 
 Compensation Range: $225K - $455K
</div>

Software Engineer, Hardware

FanDuel

<div>
 
 THE POSITION
 
 
 
 Our roster has an opening with your name on it
 
 
 At FanDuel, data is the heartbeat of our organization. As a Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will be asked to provide our business with insight and our customers with world-class personalized experiences. Every click our users make, every bet, every touchdown, every fumble, and every play is fair game for us to turn into a stream of knowledge. Your expertise will be used here to make better and faster decisions &ndash; outpacing our competition.
 
 
 Collaboration is at the core of your role. You&rsquo;ll be the linchpin between engineering teams working downstream to build out our online application and upstream to land necessary data for feature engineering. You&rsquo;ll also be working with Data Scientists and Analysts to productionize, analyze, and validate AI powered insights. You will be asked to help organize, model, and present our data as a coherent product and offer it to our stakeholders, providing a common information framework that allows FanDuel to intelligently react to what is happening on the field and in the marketplace.
 
 
 We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on &ndash; we want to hear from you!
 
 
 
 THE GAME PLAN
 
 
 
 Everyone on our team has a part to play
 
 
 <ul>
 <li>
 Designing and implementing intelligent search system incorporating typeahead search, vector search and ML personalization model signals to optimize relevance and user experience
 </li>
 <li>
 Contributing to the design and development of scalable serving systems for ML and GenAI/LLM models
 </li>
 <li>
 Developing platform features and capabilities (e.g. CLI, SDK, Infra Automation, Platform Applications) for streamlining ML Model and GenAI/LLM Application development and deployment lifecycle
 </li>
 <li>
 Business intelligence tools (e.g., Tableau, Knime, Looker)
 </li>
 <li>
 Data security and privacy (e.g. GDPR, CPP)
 </li>
 <li>
 Data governance and data testing frameworks
 </li>
 <li>
 Continuous integration and delivery of production data products
 </li>
 <li>
 An inclusive culture that expects excellence and priorities your growth as an engineer and your well-being as a person
 </li>
 <li>
 Advance your career within well-defined, skill-based tracks, either as an individual contributor or as a manager &ndash; both providing equal opportunities for compensation and advancement
 </li>
 <li>
 Collaborating with peers and sharing best practices in system reliability, automation, and data quality
 
 
 
 </li>
 </ul>
 ML engineering is a rapidly changing field &ndash; most of all, we&rsquo;re looking for someone who enjoys experimenting, keeping their finger on the pulse of current data engineering tools, and always thinking about how to do something better.
 
 
 
 THE STATS
 
 
 
 What we're looking for in our next teammate
 
 
 <ul>
 <li>
 5-7+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)
 </li>
 <li>
 1+ Years of Experience implementing vector search, semantic search, or embedding-based retrieval systems for production ML or AI applications
 </li>
 <li>
 1+ Years of Experience working with typeahead / autocomplete systems and integrating ML signals into query understanding or ranking workflows
 </li>
 <li>
 1+ Years of Experience combining outputs from multiple retrieval systems (e.g., vector search + typeahead + personalization models) to improve relevance
 </li>
 <li>
 1+ Years of experience in deploying ML and GenAI/LLM models under the constraints of scalability, correctness, and maintainability.
 </li>
 <li>
 Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, MLFlow etc.) and familiarity with LLM-specific frameworks (e.g., LangChain, Hugging Face Transformers, etc).
 </li>
 <li>
 Hands on experience with one or more ML and GenAI/LLM cloud services (Amazon SageMaker, Amazon Bedrock, Databricks Mosaic AI, Seldon, Arize, etc)
 </li>
 <li>
 4+ Years of experience designing and building various software architecture, with some emphasis on scalable architectures supporting both traditional ML and advanced LLM workflows.
 </li>
 <li>
 Deep understanding and knowledge of data structures, distributed computing, and software engineering principles
 </li>
 <li>
 3+ Years of experience demonstrating technical leadership working with teams, owning projects, defining, and setting technical direction for projects.
 </li>
 <li>
 Experience with one or more relevant tools (Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis, Terraform, Airflow)
 </li>
 <li>
 Ability to share findings in easy to consume formats, whether that is through dashboards or data modeling.
 </li>
 <li>
 Conduct regular design process reviews and ensure development standards within the team.
 </li>
 <li>
 Working with leadership to drive adoption of ML and GenAI/LLM solutions to product engineering teams.
 </li>
 <li>
 Experience working in a cloud environment such as AWS, GCP, Azure.
 </li>
 <li>
 Experience with Databricks is a plus, their unity catalog, another plus.
 </li>
 <li>
 Designing and building data pipelines for production level ML and GenAI/LLM infrastructure.
 </li>
 <li>
 Experience with vector databases to efficiently manage and retrieve embeddings for LLM applications, enabling high-performance similarity search and retrieval-augmented generation (RAG) workflows is a plus
 </li>
 <li>
 Motivate junior engineers on best practices and latest industry design patterns.
 
 
 
 </li>
 </ul>
 
 About Fanduel
 
 
 
 FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America&rsquo;s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry&rsquo;s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.
 
 
 In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.
 
 
 The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company&rsquo;s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.
 
 
 FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).
 
 
 
 Player Benefits
 
 
 
 We treat our team right
 
 
 We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO &amp; sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here:
 
 FanDuel Total Rewards
 
 . *Benefits differ across location, role, and level.
 
 
 FanDuel is an equal opportunities employer and we believe, as one of our principles states, &ldquo;We are One Team!&rdquo;. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.
 
 
 
 
 The applicable salary range for this position is $138,000 - $173,000 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.
 
 
 
 
 
 
 FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.
 
 
 
 
 
 
 It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
 
 
</div>

Senior Machine Learning Engineer

Lila Sciences

<div>
 
 Your Impact at Lila
 
 
 
 We&rsquo;re seeking a Machine Learning Research Engineer for the Open-Endedness Team with expertise in large model training and optimizing novel algorithms for best results in distributed ML infrastructure. You&rsquo;ll design and maintain large-scale training systems, optimize performance for large models, and integrate cutting-edge techniques to improve efficiency and throughput.
 
 
 Open-Endedness is an emerging area of machine learning that aims to automate never-ending innovative processes of discovery and exploration. The Open-Endedness Team, led by Ken Stanley, investigates in particular how a continual chain of deep transformative creativity can be maintained that far exceeds the derivative creativity seen in current models. In effect, the systems developed on this team will go beyond simply solving problems posed by users, to conceiving the future unimagined directions of science itself.
 
 
 
 What You'll Be Building
 
 
 
 <ul>
 <li>
 Distributed training infrastructure for LLMs and multi-modal models.
 </li>
 <li>
 Performance optimizations for large-scale model training including training and optimization workflows (SFT, RL, long-context, etc.).
 </li>
 <li>
 Orchestrate frontier and open source LLMs along with complex compute-intensive tool use
 </li>
 <li>
 Scalable pipelines for data preprocessing and experiment orchestration, including tools for efficient data loading, pipeline parallelism, and optimizer tuning.
 </li>
 <li>
 System-level performance benchmarks and debugging utilities.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Need To Succeed
 
 
 
 <ul>
 <li>
 Proven experience with distributed ML training frameworks (Megatron-LM, TorchTitan, DeepSpeed, Ray).
 </li>
 <li>
 Strong software engineering skills (Python, C++ kernel contributions are a plus).
 </li>
 <li>
 Understanding of large-scale model training techniques.
 </li>
 <li>
 Experience with cloud or HPC environments.
 
 
 </li>
 </ul>
 
 Bonus Points For
 
 
 
 <ul>
 <li>
 Prior work with scientific datasets or domain-specific modeling.
 </li>
 <li>
 Contributions to open-source ML frameworks.
 
 
 </li>
 </ul>
 
 About Lila
 
 
 
 Lila Sciences is the world&rsquo;s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai
 
 
 If this sounds like an environment you&rsquo;d love to work in, even if you only have some of the experience listed below, we encourage you to apply.
 
 
 
 We&rsquo;re All In
 
 
 
 Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
 
 
 Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
 
 
 
 A Note to Agencies
 
 
 
 
 Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science&rsquo;s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
 
 
 
 CompensationWe offer competitive compensation including bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.
 
 
 Expected Base Salary Range: $148,000 USD - $240,000 USD
</div>

Senior Machine Learning Research Engineer I/ II, Open-Endedness

Twitch

<div>
 
 About Us
 
 
 
 Twitch is the world&rsquo;s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.
 
 
 We&rsquo;re about community, inside and out. You&rsquo;ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We&rsquo;re on a quest to empower live communities, so if this sounds good to you, see what we&rsquo;re up to on LinkedIn and X, and discover the projects we&rsquo;re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.
 
 
 
 About The Role
 
 
 
 Join the Monetization ML team within Twitch's Commerce organization, where we're building the intelligent systems that power personalized experiences for creators and viewers across all monetization products. We are the team behind the ML infrastructure for ads, commerce, and money products &ndash; systems that optimize revenue and detect fraud while serving millions of users in real-time.
 
 
 From production model infrastructure to API integrations across services, we're constantly pushing the boundaries of what's possible in live streaming monetization.
 
 
 Our team are based in San Francisco, CA and Seattle, WA
 
 
 
 You Will:
 
 
 
 
 <ul>
 <li>
 Build robust ML infrastructure and platforms that power personalized monetization experiences across Twitch's ecosystem
 </li>
 <li>
 Architect and develop APIs that seamlessly integrate ML models with existing monetization services, enabling real-time and batch predictions at scale
 </li>
 <li>
 Collaborate with Applied Scientists to productionize ML models, transforming research into production-ready systems that serve millions of users
 </li>
 <li>
 Partner with product engineering teams across monetization to deliver ML-powered features that enhance creator and viewer experiences
 </li>
 <li>
 Design and implement comprehensive monitoring and operational excellence systems for ML model performance, ensuring reliability and quality at scale
 </li>
 <li>
 Develop data ingestion and processing pipelines that support both real-time inference and batch training workflows
 </li>
 <li>
 Explore and build infrastructure for emerging use cases including LLM applications in monetization contexts
 
 
 
 </li>
 </ul>
 
 You Have:
 
 
 
 
 <ul>
 <li>
 1+ years of professional software development experience with a focus on building scalable systems
 </li>
 <li>
 Experience building production ML infrastructure, including model deployment, serving, and monitoring systems
 </li>
 <li>
 Proficiency in modern programming languages (Python, Java, Go) and distributed system technologies
 </li>
 <li>
 A track record of building APIs and integrating systems that handle high-throughput, low-latency requirements
 </li>
 <li>
 Understanding of data processing pipelines and experience with streaming technologies (Flink, Kafka, or similar)
 </li>
 <li>
 Sharp problem-solving skills with a focus on algorithms, data structures, and distributed system design
 </li>
 <li>
 Bachelor's degree in Computer Science, Engineering, or equivalent real-world experience
 
 
 
 </li>
 </ul>
 
 Bonus Points
 
 
 
 
 <ul>
 <li>
 Familiarity with Twitch's tech stack: Golang, Python, Apache Flink, Cond
 </li>
 <li>
 Experience with workflow orchestration tools like Airflow or Conductor for managing ML pipelines
 </li>
 <li>
 Experience with AWS technologies like ECS, DynamoDB, Lambda, SQS, and Step Functions
 </li>
 <li>
 Knowledge of real-time ML serving systems and model deployment at scale
 </li>
 <li>
 Experience with fraud detection, recommendation systems, or monetization optimization
 </li>
 <li>
 A passion for gaming, streaming, or the Twitch platform
 
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 
 <ul>
 <li>
 Medical, Dental, Vision &amp; Disability Insurance
 </li>
 <li>
 401(k)
 </li>
 <li>
 Maternity &amp; Parental Leave
 </li>
 <li>
 Flexible PTO
 </li>
 <li>
 Amazon Employee Discount
 
 
 
 </li>
 </ul>
 
 Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 
 Job ID: TW9103
 
 
 The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
 
 
 US, WA, Seattle - Annually
 
 
 $110,500&mdash;$160,000 USD
 
 
 US, CA, San Francisco - Annually
 
 
 $127,100&mdash;$185,000 USD
 
 
 
 Twitch is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
 
 
 
 
 Twitch values your privacy. Please consult our Candidate Privacy Notice, for information about how we collect, use, and disclose personal information of our candidates.
 
</div>

Software Engineer I, Monetization ML

General Motors (GM)

<div>Job Description
The Role
The Senior Data Engineer, AI and Robotics will join the AI Research team within the Autonomous Robotics Center (ARC). This role owns the robotics data backbone that enables scalable robot learning in manufacturing &mdash; from data capture and curation through versioning, serving, and auditing. Your work will make model development reproducible, testable, and production-ready.
This is a robotics and machine learning (ML) infrastructure role, focused on multimodal robotic datasets and continuous model iteration. You will partner closely with AI researchers, robotics engineers, and plant teams to turn real-world robot behavior and failures into high-quality training data and robust production systems.
What You&rsquo;ll Do
<ul><li>Build and operate multimodal data pipelines for robotics (e.g., vision, depth, force/torque, joint states, events, metadata), including reliable capture from lab and plant-adjacent cells.
</li><li>Implement reproducible data logging and replay workflows (including ROS 2 bagging where applicable) to enable debugging, regression testing, and dataset construction.
</li><li>Own dataset lifecycle management, including versioning and lineage, provenance, governance, and data quality gates to support trustworthy model training and evaluation.
</li><li>Integrate experiment tracking and model/data traceability so teams can compare runs, reproduce results, and audit changes over time.
</li><li>Establish MLOps automation patterns (CI/CD/CT-style pipelines for ML) that reduce manual toil and increase deployment confidence for robotics AI updates.
</li><li>Partner with AI/ML, planning, and validation teams to define data contracts (schemas, labeling standards, failure taxonomies) and turn field failures into curated training datasets.
</li></ul>What You&rsquo;ll Need (Required Qualifications)
<ul><li>B.S. or M.S. in Computer Science, Computer Engineering, Data Engineering, or a related field.
</li><li>6+ years of experience building production data systems and/or ML infrastructure, with practical experience supporting training pipelines end-to-end.
</li><li>Strong proficiency in Python and at least one of: C++, Scala, or Java.
</li><li>Demonstrated engineering discipline in testing, documentation, and operational reliability.
</li><li>Experience with dataset versioning, lineage, and reproducibility tooling (e.g., DVC or equivalent approaches).
</li><li>Experience with experiment tracking and model registry patterns (e.g., MLflow or equivalent tools).
</li><li>Ability to work onsite with hardware and robotics teams, and to design pipelines that handle real-world robotic logging constraints (e.g., bandwidth limits, dropped frames, timing drift).
</li></ul>What Will Give You a Competitive Edge (Preferred Qualifications)
<ul><li>Hands-on robotics logging and replay experience (e.g., ROS 2 bags, system telemetry pipelines).
</li><li>Experience with simulation-to-real data workflows and dataset synthesis strategies.
</li><li>Familiarity with data governance requirements and auditability in safety-adjacent or safety-critical systems.
</li><li>Experience building tools to support data labeling workflows, quality assurance, and active learning loops.
</li></ul>&amp;#xa;&amp;#xa;&amp;#xa;&amp;#xa;
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day &ndash; individually and collectively &ndash; to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being&ndash;at work and at home&ndash;so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources .
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire .
Accommodations
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.</div>

Senior Data Engineer, AI&Robotics

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports &ndash; including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. 
 
Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. 
 
As a Prime Video technologist, you&rsquo;ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You&rsquo;ll get to work on projects that are fast-paced, challenging, and varied. You&rsquo;ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. 
 
We are looking for a self-motivated, passionate and resourceful Senior Software Development Engineer to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will be a technical leader helping to design and build the ML infrastructure that power our vision. You will tackle complex and ambiguous problems, designing and delivering scalable and resilient ML and Data platform solutions from the ground up. You will not only write high-quality, maintainable code, but also mentor other engineers, influence our technical strategy, and drive engineering best practices across the team. Your work will directly contribute to making Prime Video's operations more efficient and will set the technical foundation for years to come. 
 
Key job responsibilities 
As a Sr. SDE on the Prime Video Measurement Platform team, you will have deep subject matter expertise in the area of recommendation systems and ML infra. You will work with teams of scientists, product managers and engineers to translate business and functional requirements into concrete system deliverables. You will have the opportunity to build new platform services from group up, driving the development of innovative approaches to personalization, and providing opportunities for scientists and engineers to invent and implement scalable ML solutions supporting new customer experiences.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>5+ years of non-internship professional software development experience</li><li>5+ years of programming with at least one software programming language experience</li><li>5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience as a mentor, tech lead or leading an engineering team</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Sunnyvale - 193,300.00 - 261,500.00 USD annually 
USA, NY, New York - 184,900.00 - 250,200.00 USD annually 
USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually</div>

Senior SDE, Prime Video Personalization & Discovery

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