Job description

We are looking for an AI/ML Engineer to build efficient, stable foundation models for long-horizon agentic workloads. The role combines model development with systems and hardware optimization. Qualifications Strong background in machine learning, deep learning, transformers, and foundation models. Experience with PyTorch, JAX, or similar frameworks. Experience training, fine-tuning, or serving large-scale models. Knowledge of GPU architecture, CUDA, Triton, custom kernels, or hardware-aware optimization. Familiarity with distributed training and model parallelism. Experience with AWS Trainium, Inferentia, Neuron SDK, TPUs, or other custom accelerators is preferred. PhD in machine learning, computer science, electrical engineering, or a related field is preferred. Key job responsibilities Responsibilities Design, train, fine-tune, and evaluate custom foundation models. Improve model efficiency, stability, latency, throughput, and memory usage. Build models that support planning, tool use, memory, self-correction, and multi-step task execution. Optimize training and inference using CUDA, Triton, custom GPU kernels, and tensor operations. Profile and resolve compute, memory, communication, and distributed-training bottlenecks. Work with GPUs and specialized AI accelerators, including AWS Trainium and other custom tensor hardware. Develop evaluations for model reliability and long-horizon agent performance. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - Experience using Unix/Linux - Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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 amazon.jobs for more information. If the country/region you’re applying in isn’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 & AD&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 amazon.jobs . USA, TX, Houston - 142,800.00 - 193,200.00 USD annually

Requirements

Must-haves

We are looking for an AI/ML Engineer to build efficient, stable foundation models for long-horizon agentic workloads. The role combines model development with systems and hardware optimization.
Strong background in machine learning, deep learning, transformers, and foundation models.
Experience with PyTorch, JAX, or similar frameworks.
Experience training, fine-tuning, or serving large-scale models.
Knowledge of GPU architecture, CUDA, Triton, custom kernels, or hardware-aware optimization.
Familiarity with distributed training and model parallelism.
Key job responsibilities
Design, train, fine-tune, and evaluate custom foundation models.
Improve model efficiency, stability, latency, throughput, and memory usage.
Build models that support planning, tool use, memory, self-correction, and multi-step task execution.
Optimize training and inference using CUDA, Triton, custom GPU kernels, and tensor operations.
Profile and resolve compute, memory, communication, and distributed-training bottlenecks.
Work with GPUs and specialized AI accelerators, including AWS Trainium and other custom tensor hardware.
Develop evaluations for model reliability and long-horizon agent performance.
About the team
Diverse Experiences
Inclusive Team Culture
Mentorship & Career Growth
Work/Life Balance
3+ years of building models for business application experience
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience in patents or publications at top-tier peer-reviewed conferences or journals

Nice-to-haves

Experience with AWS Trainium, Inferentia, Neuron SDK, TPUs, or other custom accelerators is preferred.
PhD in machine learning, computer science, electrical engineering, or a related field is preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningawsjavapython

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave