Software Engineer II, ML Tools, Annapurna Labs
2 weeks ago
Annapurna Labs, a company acquired by AWS in 2015, is now fully integrated into the AWS infrastructure. Think of Annapurna Labs as the infrastructure provider of AWS, covering disciplines such as silicon engineering, hardware design, software, and operations.
Our portfolio includes products like AWS Nitro, ENA, EFA, Graviton, F1 EC2 Instances, AWS Neuron, Inferentia, Trainium ML Accelerators, and scalable NVMe storage.
A key role is open for a Software Engineer to lead the development of machine learning tools for optimizing and analyzing workloads. This candidate should have experience leading machine learning tool projects from architecture to delivery.
Deep knowledge of profiling, optimization, resource management, and code generation is essential. The ideal candidate will have worked on new instruction set architectures, including CPU, NPU, and GPU.
Key Responsibilities:
- Lead the design and implementation of the new toolset.
- Collaborate with developers, architects, hardware engineers, and users to ensure compatibility.
A Day in the Life:
- Design and code solutions for software architecture efficiencies.
- Create metrics, automation, and resolve software defects.
- Build impactful solutions for customers.
- Participate in design discussions, code reviews, and cross-functional collaboration.
About the Team:
We support new members with a mix of experience levels, fostering knowledge-sharing and mentorship. Career growth is a priority, and diverse experiences are valued.
AWS, the world's most adopted cloud platform, offers a culture of inclusion, growth opportunities, and work-life balance.
Continuous learning, inclusive team events, and career advancement resources are part of our commitment to becoming Earth's Best Employer.
- Hybrid Work:
We offer innovation, flexibility, and in-person collaboration, with options for in-office or hybrid work near Amazon offices.
We are open to hiring candidates in Toronto, ON, CAN.
BASIC QUALIFICATIONS
- Master's degree in computer science or equivalent.
- 5+ years of full software development life cycle experience.
- Experience in machine learning, data mining, statistics, or natural language processing.
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