Based in Seattle, WA onsite, this role designs, develops, and operates production-grade ML and LLM serving infrastructure on AWS for Amazon Connect, translating frontier research into reliable, cost-efficient AI systems. You will collaborate with scientists, engineers, and product teams to deliver AI capabilities to customers. Compensation ranges from USD 168,100 to 227,400 per year.
Responsibilities
- Design, develop, and evaluate ML systems end-to-end, converting data science prototypes into production-ready solutions that drive business outcomes.
- Build, deploy, and maintain production-grade LLM serving and inference infrastructure, delivering high-availability AI services for customers and internal teams.
- Optimize the full inference stack for performance and cost efficiency, applying techniques such as model quantization, batching strategies, KV-cache management, and accelerator tuning.
- Collaborate with cross-functional teams and customers to understand real-world challenges and translate requirements into scalable, secure, and cost-effective ML solutions on AWS.
Requirements
- 5+ years of professional software development experience (non-internship).
- 5+ years of programming experience in at least one software programming language.
- 5+ years of experience leading design or architecture of new and existing systems, including design patterns, reliability, and scaling.
- Experience as a mentor, tech lead, or leading an engineering team.
- Knowledge of machine learning and LLM fundamentals, including transformer architectures, training and inference lifecycles, and optimization techniques.
Technologies
- CUDA kernels
- GPUs
- AWS Neuron
- TPU
Benefits
- Health insurance
- Sign-on payments
- Restricted stock units (RSUs)
- 401(k) matching
- Paid time off
- Parental leave
About the Team
Amazon Web Services (AWS) is a leading, widely adopted cloud platform. AWS pioneered cloud computing and continues to innovate, earning the trust of customers—from startups to Global 500 enterprises—to power their businesses with a robust set of products and services.
Inclusive Team Culture
AWS values learning and curiosity. Employee-led affinity groups foster an inclusive environment that celebrates differences. Ongoing events and learning experiences, including Conversations on Race and Ethnicity (CORE), encourage continual engagement with our diverse community.
Work Life Balance
We prioritize work life harmony and offer flexibility to support employees at home and at work. When team members feel supported, there is nothing we cannot achieve in the cloud.
Mentorship and Career Growth
We continually raise our performance bar and provide knowledge-sharing, mentorship, and other resources to help you grow into a well-rounded professional.
Diverse Experiences
Amazon values diverse experiences. If you do not meet all preferred qualifications, we encourage you to apply. If your career is just starting, has not followed a traditional path, or includes alternative experiences, do not let that stop you from applying.
