Sr. Software Development Engineer, Neuron Explorer

Job summary

Design and build full-stack performance data collection pipelines and analysis engines to optimize machine learning workloads on Trainium and Inferentia hardware. Develop interactive visualizations and developer workflows to help customers identify and resolve performance bottlenecks in distributed training.

Job details

Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. AWS Neuron is the complete software stack for the AWS Trainium and Inferentia cloud-scale machine learning accelerators and the Trn3/Trn2/Trn1 and Inf2/Inf1 servers that use them. This role is for a Sr. Software Development Engineer on the Developer Experiences (DevEx) team within AWS Neuron, based in Toronto. The Neuron Explorer team makes AWS Trainium performance visible. We own Neuron Explorer, the tool for profiling, debugging, and optimizing machine learning workloads on Trainium and Inferentia. We build profiling, debugging, and analysis tools that let engineers see how efficiently models and kernels use the hardware, pinpoint bottlenecks, and decide what to optimize next. Neuron Explorer traces execution from source code down to hardware operations across both single-node and distributed applications. Our goal is to cut through complex execution data so customers can optimize faster and reach higher performance on Trainium. As a Sr. Software Development Engineer for the Neuron Explorer team, you will design, build, and operate the full stack behind Neuron Explorer — from low-level performance data collection and analysis engines to interactive visualizations and developer workflows. You will own features end to end, spanning the backend processing pipeline, the web UI, and the CLI, and you will help push our AI-powered recommendation and analysis capabilities that automatically surface bottlenecks and guide optimization. Key job responsibilities - Design and build performance data collection pipelines and analysis engines that transform raw hardware execution data into actionable insights for Neuron Explorer users. - Develop interactive visualizations and developer workflows that make complex profiling data understandable, helping customers pinpoint bottlenecks across single-node and distributed training workloads. - Own features end to end across the full software development lifecycle — from scoping and design through implementation, testing, deployment, and operations — ensuring reliability and maintainability. - Collaborate with compiler, runtime, and chip architecture teams to surface the right performance information so internal and external customers can optimize AI workloads on Trainium and Inferentia hardware. - Evaluate and integrate generative AI capabilities into Neuron Explorer's recommendation engine, building features that automatically identify optimization opportunities and guide customers toward higher performance. A day in the life You will work across the backend processing pipeline, the web UI, and the CLI that make up Neuron Explorer, partnering with compiler, runtime, and chip architecture teams to expose the data customers need to optimize their models. You will work with senior technical leaders and management to define product direction and deliver it to customers, including teams bringing massive-scale multi-modal large language models to peak performance on Trainium. We build the full stack of software, servers, and chips to accelerate machine learning at the highest scale. About the team Inclusive Team Culture Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences. Work/Life Balance Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Basic Qualifications: - 5+ years of non-internship professional software development experience - Experience as a mentor, tech lead or leading an engineering team - Bachelor's degree in computer science or equivalent Preferred Qualifications: - Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution - Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware - Experience with PyTorch, JIT compilation, and AOT tracing - 6+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations [https://amazon.jobs/content/en/how-we-hire/accommodations] for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status. CAN, ON, Toronto - 150,700.00 - 251,700.00 CAD annually

What you’ll do

Design and build full-stack performance data collection pipelines and analysis engines to optimize machine learning workloads on Trainium and Inferentia hardware. Develop interactive visualizations and developer workflows to help customers identify and resolve performance bottlenecks in distributed training.

Requirements

Requires at least 5 years of professional software development experience and a bachelor's degree in computer science or equivalent. Preferred candidates have experience with machine learning fundamentals, LLM deployment, and performance optimization on AI acceleration hardware.

Benefits

• Health insurance
• Medical insurance
• Dental insurance
• Vision insurance
• Prescription insurance
• Basic life insurance
• AD&D insurance
• Registered retirement savings plan
• Deferred profit sharing plan
• Paid time off
• Restricted stock units

Listed skills

• Machine learning · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Software development
• Machine learning
• Large language models
• Performance profiling
• Debugging
• System optimization
• PyTorch
• JIT compilation
• AOT tracing
• Distributed systems
• Hardware acceleration
• Data pipelines
• Web UI development
• CLI development
• Technical leadership
• Mentoring
• Management
• Operations
• Reliability
• Workflow Management
• Innovation
• Machine Learning
• Amazon Web Services
• Generative Artificial Intelligence
• Computer Science
• Maintainability
• Full Stack Development
• Node.js (Javascript Library)
• Code Review
• Software Development Life Cycle
• Software Development
• Time Off Management
• Medical Prescription
• PyTorch (Machine Learning Library)
• Version Control
• Building Codes
• Command-Line Interface
• Large Language Modeling
• Restricted Stock
• Recommender Systems
• Distributed Machine Learning
• Web UI

Job areas

• Software
• Technology
• Engineering
• Data & Analytics
• Software Development Engineer
• Software Developer / Engineer
• Software Developers

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