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About the Role
Join the Toronto Neuron team (Annapurna Labs) to optimize machine learning models for AWS Trainium and build industry-leading profiling tools. Interns will solve real customer and engineering problems with mentorship from experienced engineers.
Responsibilities
- Bring up and optimize state-of-the-art machine learning models for peak performance on AWS Trainium.
- Build industry-leading profiling tools to help engineers identify and fix bottlenecks.
- Take newly released machine learning models from first bring-up to peak performance on current and next-generation AWS Trainium silicon.
- Write and tune kernels, optimize sharding and model execution.
- Build benchmark and measurement infrastructure.
- Tackle architectural bottlenecks that shape future Trainium designs.
- Turn ideas into reusable Neuron components and optimization techniques.
- Make AWS Trainium performance visible through profiling, debugging, and analysis tools.
- Build low-level performance data collection, analysis engines, interactive visualizations, or developer workflows.
- Cut through complex execution data so customers can debug faster and reach higher performance on Trainium.
Requirements
- Currently enrolled in a Bachelor's degree program or higher in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
- Programming experience through coursework, research, or a previous internship using Python, C, and/or C++.
- Strong interest and academic, research, or project experience in at least two of the following areas: Performance engineering, profiling, benchmarking, or low-level systems optimization; Kernel development, parallel programming, or computer architecture; Developer tooling, including profilers, debuggers, diagnostics, or visualization; Data structures and algorithms; Machine learning frameworks and models, including PyTorch or JAX; Compiler or ML systems technologies such as LLVM, MLIR, XLA, or TVM.
- Experience bringing up and optimizing machine learning models.
- Experience writing or optimizing kernels for GPUs, ML accelerators, or FPGAs.
- Experience using performance analysis tools or building developer tools.
- Previous technical internship or relevant research experience.
- Experience with full stack development, including front-end technologies such as TypeScript and React, and back-end services (experience with Go is a plus).
- Ability to explain technical challenges and solutions clearly.
- Ability to independently work through ambiguous or undefined problems and think abstractly.
- Experience in developing agentic workflows for work automation.
Skills
- Python
- C
- C++
- Performance engineering
- Profiling
- Benchmarking
- Low-level systems optimization
- Kernel development
- Parallel programming
- Computer architecture
- Developer tooling
- Profilers
- Debuggers
- Diagnostics
- Visualization
- Data structures
- Algorithms
- Machine learning frameworks
- Machine learning models
- PyTorch
- JAX
- Compiler technologies
- ML systems technologies
- LLVM
- MLIR
- XLA
- TVM
- TypeScript
- React
- Go
Location
- Toronto, ON, CAN
Work Type
- Internship
Experience Level
- Intern
Education Level
- Bachelor's degree or higher in Computer Science, Computer Engineering, Electrical Engineering, or a related field
Salary/Compensations
- 100,810.00 CAD Annually
Benefits
- Basic life & AD&D insurance
- Paid time off
- Other resources to improve health and well-being
About the Company
- Annapurna Labs designs the custom silicon at Amazon, including Graviton, Trainium, Inferentia, and the Nitro system.
- The team owns the full stack, from silicon through the software that makes it work (compilers, runtimes, drivers, and frameworks).
Equal Opportunity
- Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
- 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.