Amazon Machine Learning Engineer Model Customization 

United Kingdom, England, London 

109401801

Key job responsibilities
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
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.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

- Experience (non-internship) in professional software development
- Experience in professional, non-internship software development
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- • 3+ years of non-internship professional software development experience, design or architecture (design patterns, reliability and scaling) of new and existing systems experience, programming with at least one software programming language
- • Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference) and with generative AI technology

- Bachelor's degree in computer science or equivalent
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- • 2+ 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
- • 1+ years of experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework