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# Sr. Firmware Engineer, Annapurna Labs, Machine Learning Acceleration - Power and Performance

- **Company:** Amazon.com, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $193,300.0 - $261,500.0
- **Contract:** Internship / Graduate position
- **Skills:** Algorithm Design, Automation of Tests, Software Quality, Code Review, Data Structures, Software Debugging, Programming Tools, Firmware, Hardware Interface Design, Python (Programming Language), Machine Learning, Performance Tuning, Software Engineering, Software Systems, System Programming, Scripting, State Machines, Information Technology, Optimization Algorithms, Performance Monitor, Data Pipelines
- **Published:** July 22, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/27869202/Sr-Firmware-Engineer-Annapurna-Labs-Machine-Learning-Acceleration-Power-Performance-Texas-Austin-7375

## About the Role

5+ years of non-internship professional software development experience

 - Experience as a mentor, tech lead or leading an engineering team
 - Bachelor's degree in computer science, electrical engineering, or related field
 - Strong firmware or embedded systems development experience
 - Proficiency in C/C++ for systems programming with strong foundation in algorithms and data structures
 - Experience implementing efficient algorithms in resource-constrained, real-time environments
 - Experience with hardware interfaces, instrumentation, or performance monitoring
 - Strong debugging skills with hardware-software systems
 - Experience building developer tools or instrumentation frameworks, Experience developing control algorithms, optimization algorithms, or state machines in firmware
 - Experience with power management algorithms, thermal control policies, or dynamic performance optimization
 - Background in tracing frameworks, telemetry systems, or performance analysis
 - Understanding of algorithmic complexity and optimization techniques for embedded systems
 - Familiarity with hardware performance counters, on-chip monitoring, or hardware debug interfaces
 - Experience with data collection pipelines and scripting (Python, shell) for algorithm validation
 - Understanding of ML training/inference workloads and their performance characteristics
 - Takes strong ownership, works effectively in ambiguous situations, demonstrates a bias for action while consistently delivering impactful results

## Description

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 and implement on-device tracing and telemetry collection systems to support algorithm development and validation
 - Build developer tools and data pipelines for metric collection, analysis, and visualization of algorithm behavior
 - Implement low-overhead instrumentation that minimizes impact on workload performance
 - Collaborate with hardware architects to understand hardware capabilities and identify optimal instrumentation points
 - Develop automated testing and validation workflows; integrate with optional cloud-based analytics pipelines
 - Own firmware code quality through rigorous testing, debugging, and validation on hardware

A day in the life
You will work closely with power architects and hardware teams to understand silicon capabilities, implement low-level control mechanisms, and create the algorithms and tooling that deliver optimal system behavior.

This position is ideal for firmware engineers who enjoy solving algorithmic challenges in resource-constrained environments, working close to hardware, and building systems that intelligently manage complex trade-offs in real-time.

About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.


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