Senior ML Engineer Generative AI Innovation Center

The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists scientists engineers and architects collaborates with customers across industries to finetune and deploy customized generative AI applications at scale. Additionally we work closely with foundational model providers to optimize AI models for Amazon Silicon enhancing performance and efficiency.

As an Senior ML Engineer on our team you will work with clients partners and other AWS teams to drive the development of custom Large Language Models (LLMs) across languages domains and modalities. You will be responsible for finetuning stateoftheart LLMs for diverse use cases while optimizing models for highperformance deployment on AWSs custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI tackling endtoend LLM training pipelines at massive scale and delivering nextgeneration AI solutions for top AWS clients.

As an Amazonian leader you will demonstrate the Amazon Leadership Principles coaching and mentoring others on best practices performance and career development. You must be comfortable leading others and driving work rather than being part of the team. If you love to learn and want to innovate in the world of generative AI Generative AI Innovation and Delivery is the right place for you.

Key job responsibilities
LargeScale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed ensuring scalability and efficiency
LLM Customization & FineTuning: Adapt LLMs for new languages domains and vision applications through continued pretraining finetuning and Reinforcement Learning with Human Feedback (RLHF)
Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance
Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges codeveloping tailored generative AI solutions
Define path to production for generative AI solutions and implement large scale production generative AI solutions.

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 hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats 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 its in our nature to learn and be curious. Our employeeled 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 (gender diversity) conferences inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledgesharing mentorship and other careeradvancing resources here to help you develop into a betterrounded professional.

Work/Life Balance
We value worklife 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 theres nothing we cant achieve in the cloud.

5 years of professional software development and machine learning experience
Proficiency in at least one programming language
Experience mentoring engineers leading technical initiatives or managing an engineering team
Handson experience with deep learning and machine learning methods (e.g. for training fine tuning and inference)
Experience with design development optimization and productionization of generative AI solutions algorithms or technologies


Bachelors degree in Computer Science or equivalent
Handson experience with at least one ML library or framework
2 years of professional experience in developing deploying or optimizing ML models in production
5 years of professional experience in the full software development life cycle including coding standards code reviews source control management build processes testing and operations


Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect use and transfer the personal data of our candidates.

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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.