Machine Learning Engineer, Workforce Solutions - Analytics and Tech

- 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 programming with at least one software programming language
- 3+ 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

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
The Workforce Solutions Analytics and Tech team is actively seeking candidates who are interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence (AI). We are looking for a talented AI and Machine Learning (ML) engineer with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact. Your contributions will be instrumental to tackle staffing challenges within Amazon's warehouses.
As a member of our team, you'll work on projects that directly impact over a million Amazon associates. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.

The types of initiatives you can expect to work but not limited to include:

Developing personalized recommendation systems.

Key job responsibilities
- Design, implement, and productionize AI/ML models by working very closely with scientists on the team.
- Develop ML/LLM workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure a high bar for the quality of architecture and design of our AI ML systems and data infrastructure
- Leverage AWS AI services and other internal / publicly available external tools & services to accelerate our AI investments
- Detail-oriented, always backs up ideas with facts. Understands complex application data flows and bridge the gap between technical and business app requirement
- Identify state of the art models / solutions to enable new capabilities for code migration and code testing, drive down tech debt and increase operational efficiency
- Share expert knowledge in performance, large scale distributed system scalability, system architecture, and engineering best practices
- Provide thought leadership and hands-on support in selecting, defining, training and fine-tuning Large Language Models (LLMs), prompt engineering, and other GenAI efforts.
- Mentor other engineers, especially on AI/ML initiatives, and foster a culture of learning & collaboration.
- Define data and feature validation strategies
- Deploy models to production systems and operate them including monitoring and troubleshooting

A day in the life
As a Machine Learning Engineer, you will work closely with science teams to bring research to production. This is a role that combines engineering knowledge, technical strength, and product focus. It will be your job to implement novel ML systems, product integrations, and performance optimizations. You will guide the direction of a MLOPS automation framework via collaboration with the engineering and research communities.
You will collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems and you will provide support for business continuity on a rotating on call.