Member Technical Staff - Reinforcement Learning Simulation Agi Autonomy jobs at Amazon in United States, San Francisco

Key job responsibilities
- Design and implement highly scalable and realistic simulation environments for training agents using reinforcement learning.
- Develop and deploy generative AI approaches to automate the creation of diverse and complex simulation environments and scenarios.
- Analyze, troubleshoot, and profile complex machine learning systems within the simulation context, identifying and resolving performance bottlenecks.

- PhD, or Master's degree or 5+ years of applied research experience
- Experience programming in C++, Python or related language
- Experience with simulation and synthetic data generation
- Experience with neural deep learning methods and machine learning

- PhD in Computer Science, Machine Learning, or a related field
- 3+ years' experience building machine learning models (includes internships)
- Demonstrated experience in developing and implementing simulation environments or synthetic data generation for reinforcement learning.
- Strong programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch
- Excellent problem-solving skills, with the ability to think creatively and critically about complex problems
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teamsPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Key job responsibilities
You will contribute directly to AI agent development in an applied research role, including model training, dataset design, and pre- and post-training optimization. You will be hired as a Member of Technical Staff.

- 3+ years' experience building machine learning models
- Proficiency in Python, Java, C++, or related language
- Experience with deep learning methods and tools, e.g., PyTorch, JAX

- PhD or Master's degree in computer science or related field
- Strong background in scientific research with a proven ability to generate and implement new ideas in machine learning
- Willingness to step outside typical role boundaries to get things done — every member of technical staff is expected to write code, design experiments, and interpret results
- Ability to communicate results and insights to both technical and non-technical audiences, including through presentations and written reports
- Ability to think big about the arc of development of AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems
- Capacity to mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the teamPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Key job responsibilities
* Design, build, and deploy machine learning models, frameworks, and data pipelines
* Optimize ML training, inference, and evaluation workflows for reliability and performance
* Evaluate and improve ML model performance and metrics
* Develop tools and infrastructure to enhance ML development productivity

* 3+ years experience building and deploying machine learning systems
* Experience with ML frameworks (e.g. PyTorch, TensorFlow) and ML orchestration tools
* Proven track record of improving ML systems, performance, and workflows

* Experience building and optimizing production-grade AI systems, e.g., for self-driving, simulation, or LLM applications
* Willingness to step outside typical role boundaries to get things done — every member of technical staff is expected to write code, design experiments, and interpret results
* Capacity to work autonomously and with a small team to drive research progressPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

In this role, you will work closely with research teams to design, build, and maintain systems for training and evaluating state-of-the-art agent models.Key job responsibilities* Evaluate performance of the training infrastructure, diagnose problems and address any gaps that exist.
* Develop reliable infrastructure to schedule training and model evaluation jobs across clusters.
* Work closely with researchers to create new techniques, infrastructure, and tooling around emerging research capabilities and evaluating models to meet customer needs.
* Manage project prioritization, deliverables, timelines, and stakeholder communication.
* Illuminate trade-offs, educate the team on best practices, and influence technical strategy.
* Operate in a dynamic environment to deliver high quality software.

5+ years of non-internship professional software development experience
5+ years of programming with at least one software programming language experience
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience as a mentor, tech lead or leading an engineering team

5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent
Excellent knowledge of theory and practice of MLPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.Key job responsibilities
- Develop and execute monitoring and maintenance of test equipment including mechanical, electrical, pneumatic, and vacuum systems
- Troubleshoot and repair failed or faulty components
- Design and implement automated control systems and safety interlocks
- Support day to day operations of HITL venues, including configuration management
- Assemble and deliver test racks including servers, data acquisition systems, sensors, actuators, and thermal control
- Follow ESD, low and high voltage, vacuum, and other safety protocols

- Experience in a Linux or Unix environment
- Experience troubleshooting and debugging technical systems
- Can lift and rack equipment up to 40 pounds
- 2+ years experience with electronics test equipment

- Experience configuring, deploying, and testing software updates, including the ability to identify issues and escalate to development as appropriate
- Experience working with hardware and software teams for setting up, testing, and troubleshooting prototype devices
- Experience scripting in modern programming languages
- 2+ years of demonstrating safety standards experience
- Experience in process design and documentation
- Experience with vacuum systems and high pressure inert gases

Key job responsibilitiesThe ideal candidate is passionate about new opportunities and has a demonstrable track record of success in delivering new features and products. A commitment to team work, hustle, and strong communication skills (to both business and technical partners) are absolute requirements. Creating reliable, scalable, and high performance AI products requires exceptional technical expertise, a sound understanding of the fundamentals of Computer Science and Machine Learning. This person has thrived and succeeded in delivering high quality technology products/services in a hyper-growth environment.

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

In this role, you will work closely with research teams to design, build, and maintain systems for training and evaluating state-of-the-art agent models.Key job responsibilities
* Develop cutting-edge training infrastructure to ensure large-scale reinforcement learning on LLMs runs highly efficient and robust.
* Work across the entire technology stack, including low level ML system, job orchestration and data management.
* Analyze, troubleshoot and profiling complex ML systems, identify and address performance bottlenecks.
* Work closely with researchers, conduct MLSys research to create new techniques, infrastructure, and tooling around emerging research capabilities.

- PhD, or Master's degree and 3+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience debugging ML systems

- PhD in Computer Science, Machine Learning, or a related field, with a focus on ML System.
- Demonstrated experience in developing, implementing and debugging large scale ML systems.
- Experience with distributed system, Megatron, vLLM, Ray, and working with GPUs.
- Experience with patents or publications at top-tier peer-reviewed conferences or journals.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.