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

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$207K-$280K not verified - source not recorded; timestamp not recorded

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

109% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

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About this role

Principal Product Manager - Kernels, AI/ML, Annapurna Labs Cupertino, California, USA 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,

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