Senior ML Compiler Engineer — NKI for Trainium

Amazon Web Services (AWS); Seattle (WA); On-site; USD 168,000 - 227,000; Full time

Benefits offered by this job

RSUs

Health insurance

Job summary

Annapurna Labs (U.S.) Inc. in Seattle seeks a Sr. Machine Learning Compiler Engineer to lead ground-up development of a high-performance compiler for the largest ML workloads. You will architect features, publish cutting-edge work, and mentor a team of experienced engineers in a hands-on role.

The position requires deep ML accelerator background and strong collaboration with AWS ML teams to scale solutions across multiple products and services. Relocation to Seattle is expected.

Qualifications

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

Responsibilities

• You will be a thought leader supporting the ground-up development and scaling of a compiler for the world’s largest ML workloads.
• Architecting and implementing business-critical features, publishing cutting-edge work, and mentoring a team of experienced engineers.
• Collaborate with AWS ML teams and contribute to technical communications and hand-on work.

Skills

Software development

Programming languages

System design

SDLC

Education

Bachelor's degree

Tools

NKI

Job description

Annapurna Labs (U.S.) Inc. in Seattle seeks a Sr. Machine Learning Compiler Engineer to lead ground-up development of a high-performance compiler for the largest ML workloads. You will architect features, publish cutting-edge work, and mentor a team of experienced engineers in a hands-on role.

The position requires deep ML accelerator background and strong collaboration with AWS ML teams to scale solutions across multiple products and services. Relocation to Seattle is expected.