Senior ML Engineer, Generative AI Innovation Center

Job description

Description

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 fine-tune 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 fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS’s custom AI accelerators.

This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation 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

• Large-Scale 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 & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, 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, co-developing 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, 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 (gender diversity) 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.

Basic Qualifications

• 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

• Hands-on 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



Preferred Qualifications

• Bachelor's degree in Computer Science or equivalent

• Hands-on 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 ( https://www.amazon.jobs/en/privacy_page ) 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information.

If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Required Skill Profession

Other General