Lead Software Engineer - AI/ML, AWS Neuron Distributed Training

Salary: $151,300 - 261,500 per year Requirements:

• Bachelor's degree in computer science or a related field
• Minimum of 5 years of professional software development experience (not including internships)
• At least 5 years of programming experience in at least one software language
• Proven experience leading design or architecture of new and existing systems, focusing on design patterns, reliability, and scalability for 5 years
• Comprehensive knowledge of the full software development lifecycle, including coding standards, code reviews, source control management, build processes, testing, and operations for 5 years
• Experience mentoring, leading a tech team, or directing engineering projects
• Solid background in machine learning, large-scale training with large language models (LLMs), and expertise in PyTorch

Responsibilities:

• In this role, you will take the lead on integrating distributed training support within PyTorch, the Neuron compiler, and runtime stacks. You will implement distributed training strategies and utilize them to enhance model optimization, achieving optimal performance and efficiency on our custom AWS silicon, including Trainium servers. Strong software development skills, the capability to dive deep into technical challenges, and effective collaboration within cross-functional teams are essential for your success in this position.

Technologies:

• AWS
• Cloud
• Hardware
• Support
• Machine Learning
• PyTorch
• DevOps
• EC2
• LLM
• OSS
• TensorFlow
• Web

More:

At Annapurna Labs, we design silicon and software that drives innovation forward. Our customers rely on us to develop cloud solutions that tackle challenges previously deemed insurmountable. Our custom chips and software enable us to confront unprecedented technical hurdles and deliver transformative results.

The AWS Neuron software stack supports our cloud-scale Machine Learning accelerators, Trainium and Inferentia. As a member of the Distributed Training team, you will collaborate closely with chip architects, compiler engineers, and runtime engineers, focusing on the development, enablement, and fine-tuning of various ML model families.

Originally a startup acquired by AWS in 2015, we now integrate seamlessly into AWS's infrastructure offerings. Our team comprises diverse skills across silicon engineering, hardware design, software, and operations. We are committed to fostering an environment of mentorship and knowledge-sharing among our team members.

At AWS, we value diverse backgrounds and experiences, welcoming applicants from all paths, even if they do not meet every qualification. Our inclusion and flexibility principles ensure a supportive cultural environment where every individual can thrive.

As we strive to be Earth’s Best Employer, expect abundant growth opportunities through mentorship and shared knowledge. We offer a comprehensive compensation package that reflects the labor market, integrating salary and benefits tailored to individual candidates.

last updated 37 week of 2026