Lead SDE, ML Profiling & Performance Tools

Amazon Inc.; Omaha, Northern (NE, KY); Hybrid; USD 168,000 - 262,000; Full time

Benefits offered by this job

RSUs

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Annapurna Labs is seeking a Sr. Software Development Engineer to lead the Neuron Core Tools team, delivering profiling and optimization tools for Neuron ML accelerators.

You will collaborate with hardware and software teams to ensure tools enable performance profiling of large ML workloads and identify bottlenecks. Responsibilities include mentoring, coordinating with frameworks and compiler teams, and shaping tool roadmap to improve efficiency at scale.

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 of new and existing systems (design patterns, reliability, scaling).
• 5+ years of full software development life cycle, including coding standards, reviews, source control, build, testing and operations.
• Experience as a mentor, tech lead or leading an engineering team.

Responsibilities

• Provide technical leadership to the Neuron Core Tools team.
• Work closely with the frameworks and compiler teams.
• Collect requirements from training, inference and runtime teams.
• Collaborate with the compiler performance team to ensure timely release of core tools.
• Anticipate future needs based on the product roadmap and develop tools to increase efficiency in large-scale compute.

Skills

Software development

Programming languages

Design/architecture leadership

SDLC

Mentorship/leadership

Education

Bachelor's degree in computer science

Job description

Amazon Annapurna Labs is seeking a Sr. Software Development Engineer to lead the Neuron Core Tools team, delivering profiling and optimization tools for Neuron ML accelerators.

You will collaborate with hardware and software teams to ensure tools enable performance profiling of large ML workloads and identify bottlenecks. Responsibilities include mentoring, coordinating with frameworks and compiler teams, and shaping tool roadmap to improve efficiency at scale.