Principal Product Manager - Kernels, AI​/ML, Annapurna Labs

Description
AWS Neuron is looking for an experienced Technical Product Manager to define and drive product strategy for the Neuron Kernel Interface (NKI), a compiler library enabling custom kernel development and optimization. You will be part of the AWS Neuron Product Management team, driving innovation in machine learning acceleration software. AWS Neuron is the software stack for Trainium and Inferentia, the AWS Machine Learning chips, delivering best-in-class ML performance in the cloud.

You will lead NKI requirements working backward from customer needs, drive kernel library features definition, and drive developer experience for custom kernel development, enabling customers to successfully and independently develop and optimize ML workloads on AWS Neuron through deep understanding of compiler systems, kernel optimization, and hardware acceleration.

Description
AWS Neuron is looking for an experienced Technical Product Manager to define and drive product strategy for the Neuron Kernel Interface (NKI), a compiler library enabling custom kernel development and optimization. You will be part of the AWS Neuron Product Management team, driving innovation in machine learning acceleration software. AWS Neuron is the software stack for Trainium and Inferentia, the AWS Machine Learning chips, delivering best-in-class ML performance in the cloud.

You will lead NKI requirements working backward from customer needs, drive kernel library features definition, and drive developer experience for custom kernel development, enabling customers to successfully and independently develop and optimize ML workloads on AWS Neuron through deep understanding of compiler systems, kernel optimization, and hardware acceleration.
The ideal candidate will have solid understanding of compiler technologies, computer architecture, and ML systems. They should be able to assess technical implications of compiler architecture decisions, understand customer needs, and drive developer experience strategy.

Experience with ML frameworks, model architectures, and distributed computing is highly valuable.
Additionally,

The Ideal Candidate Should Have

• Proven track record of driving product strategy and owning roadmap definition in complex technical environments
• Experience delivering features with deep understanding of technical trade-offs and product implications
• Strong ability to contribute to and influence engineering discussions around technology decisions and strategy
• Demonstrated success in representing customer needs and driving alignment during executive-level prioritization
• Track record of delivering results in fast-paced, ambiguous environments, particularly in early-stage programs
• Experience with modern software development and collaborative open-source projects

About AWS Neuron
AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks.

Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrocks, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.
Key job responsibilities
In This Role, You Will

• Drive and execute product strategy and roadmap working backwards from customer requirements in collaboration with engineering technical leadership
• Assess technical implications of product architecture and optimization decisions
• Drive technical alignment across Neuron components, Neuron workflows and dependencies
• Work directly with software engineering teams to define and execute on new features
• Produce clear and concise documents such as PRFAQ and PRD documents
• Write user stories, and validate features meet developer needs
• Drive feature discussions with customers, engineering, and other stakeholders
• Anticipate bottlenecks, manage risk and escalations, balancing…