The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer with a strong machine learning background, to build capabilities such as fine tuning, distillation, and LLM Inference.

As a ML engineer with the Alexa AI team, you will be responsible for machine learning platform focus on LLM training, production deployment, and optimizations to advance the state of LLMs. You will collaborate closely with Applied Scientists and other MLEs, leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development of Generative Artificial Intelligence solutions.

Key job responsibilities
The 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.

Responsibilities-

• Will work with other team engineers to investigate design approaches, prototype new technology and evaluate technical feasibility.
• Work closely with Applied scientists to process data, scale machine learning models
• Will work in an Agile/Scrum environment to deliver high quality software.

About the team
Central Analytics and Research Science (CARS) is an analytics, software, and science team within Amazon's Alexa AI organization. Our mission is to provide scalable and reliable evaluation of the state-of-the-art Conversational AI on how customers perceive the assistants they interact with – from the metrics themselves to software applications to deep dive on those metrics – allowing assistant developers to improve their services.

Basic Qualifications

• 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 working with Py Torch or JAX software
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field

Preferred Qualifications

• Experience working with Py Torch or JAX software, or experience with vLLM, SGLang, TensorRT or similar platforms in production environments
• Experience developing large model hosting platforms, establishing frameworks, and scaling and optimizing inference system.
• Experience developing and maintaining MLOps tool in large organizations.

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 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.

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 https://amazon.jobs/en/benefits.

USA, MA, Boston - 143,700.00 - 194,400.00 USD annually