Firmware Engineer, Annapurna Labs, ML Acceleration - Performance Instrumentation & Developer Tools
Amazon - Austin, Texas, USA
Posted Nov 3, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- 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
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- 401(k) match
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Schedule
- Shift type
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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
State eligibility is not yet verified.
About this role
Firmware Engineer, Annapurna Labs, ML Acceleration - Performance Instrumentation & Developer Tools Austin, Texas, USA AWS Utility Computing (UC) provides product Annapurna Labs (our organization within AWS UC) 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. We are seeking a Senior Firmware Engineer to join our Power Architecture team, developing firmware algorithms for power and performance management on ML Acceleration Chips. In this role, you will design and implement intelligent control algorithms, optimization strategies, and real-time decision-making systems that maximize performance while managing power and thermal constraints. You will develop sophisticated firmware that monitors system state, makes dynamic trade-offs between power and performance, and implements adaptive control policies. To enable this work, you will also build instrumentation and tracing capabilities that provide the telemetry needed to develop, tune, and validate your algorithms, with collected data optionally post-processed using cloud-based analytics. Key job responsibilities - Design and implement firmware algorithms for power management, thermal control, and performance optimization on ML acceleration hardware - Develop real-time control policies and state machines that dynamically balance power, thermal, and performance constraints - Create optimization algorithms for resource allocation, frequency/voltage scaling, and workload scheduling - Implement efficient data structures and algorithms suitable for embedded, resource-constrained environments - Design
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