Sr. Machine Learning Engineer, Special Projects
Job Description
Sr. Machine Learning Engineer, Special Projects at Amazon.com Services LLC in Seattle, WA (onsite); salary USD 168,100 - 227,400 per year.
Responsibilities
- Spearhead large-scale technical initiatives and make critical architectural decisions
- Identify and resolve complex technical challenges, often in ambiguous problem spaces
- Design and implement scalable data processing pipelines and infrastructure to support ML model training workflows
- Develop tools for data preprocessing, feature engineering, and efficient resource utilization for large-scale AI training jobs
- Create monitoring systems, debugging tools, and performance optimization solutions for ML infrastructure
- Collaborate to integrate ML frameworks with production systems and implement version control for both code and model artifacts
- Mentor and guide MLEs and SDEs, fostering their growth and the overall team’s capabilities
Requirements
- 5+ years of professional software development experience (non-internship)
- 5+ years of programming experience in at least one programming language
- 5+ years of experience leading design or architecture of new and existing systems, including design patterns, reliability, and scalability
- Experience as a mentor, tech lead, or leading an engineering team
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Parental leave
About the Team
- We represent Amazon's ambitious vision to solve the world's most pressing challenges. We operate with the agility of a startup while backed by Amazon's resources and operational excellence.
- We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
- Our team is for engineers who enjoy teamwork, cross-functional collaboration and building new things.
- You need to be a fast learner able to independently disambiguate requirements.
A Day in the Life
- Our main data consumers and producers are science teams.
- You will work closely with scientists from various domains to clarify requirements, design new systems, upgrade existing services, and provide operational support to mitigate issues.
- Your work will largely involve data services and pipelines.