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

About the role

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.

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
• 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

Requirements

• 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

Qualifications

• Experience developing control algorithms, optimization algorithms, or state machines in firmware
• Background in tracing frameworks, telemetry systems, or performance analysis
• Familiarity with algorithmic complexity and optimization techniques for embedded systems
• 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