Edge ML Integration Engineer for Wearable Sensor Algorithms

WHOOP; Boston (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

WHOOP is seeking an Edge Algorithm Integration Engineer to bring Sensor Intelligence algorithms from reference implementations to production on WHOOP devices. You will translate and optimize algorithms for embedded hardware and collaborate across Sensor Intelligence, Firmware, Edge ML Platform, Mobile, Cloud, and Connectivity teams.

You will ensure numerical equivalence, profile performance on device, and build reusable tools to accelerate future migrations, balancing compute, memory, latency

Qualifications

• BS/MS in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field.
• Strong C/C++ software development experience with embedded, real-time, or resource-constrained systems, including memory management, compute, latency, and power considerations.
• Experience porting, integrating, or optimizing signal-processing or machine-learning algorithms for MCU-based, embedded, or edge platforms, including translating Python, MATLAB, or similar reference environments.
• Experience profiling and optimizing embedded software for runtime, memory footprint, computation, and/or power, with strong debugging across algorithm and systems boundaries.
• Strong systems thinking and software integration skills for cross-team collaboration to resolve technical issues.
• Experience with DSP optimization, fixed-point implementation, quantization, model compression, ARM Cortex-M, DSPs, NPUs, RTOS, CMSIS-DSP/CMSIS-NN, or TensorFlow Lite Micro.
• Experience with physiological sensing, wearable devices, time-series sensor data, low-power systems, or verifying algorithm equivalence is a plus.
• Commitment to leveraging AI tools in day-to-day tasks with high-quality output.

Responsibilities

• Own end-to-end porting of Sensor Intelligence algorithms from reference environments to production-ready implementations on WHOOP embedded platforms.
• Translate Python, MATLAB, and other references into efficient production-quality C/C++, optimizing signal-processing and ML algorithms for compute, memory, latency, power, and real-time execution.
• Understand architecture, data flow, runtime requirements, and dependencies across cloud, mobile, connectivity, and sensor pipelines; resolve dependencies for on-device execution.
• Integrate algorithms with firmware, sensor pipelines, and Edge ML platform capabilities, defining interfaces, requirements, and system behavior.
• Establish numerical equivalence between reference and edge implementations, profile on-device performance, and debug complex issues spanning algorithms and hardware.
• Build reusable tools, test harnesses, profiling infrastructure, and deployment patterns to accelerate future migrations across WHOOP hardware.

Skills

C/C++ development

Embedded/RTOS systems

Algorithm porting to edge

Performance profiling

Debugging across boundaries

Education

BS/MS in Computer Engineering, Electrical Engineering, CS

Tools

CMSIS-DSP/CMSIS-NN

TensorFlow Lite Micro

ARM Cortex-M

DSP optimization techniques

Job description

WHOOP is seeking an Edge Algorithm Integration Engineer to bring Sensor Intelligence algorithms from reference implementations to production on WHOOP devices. You will translate and optimize algorithms for embedded hardware and collaborate across Sensor Intelligence, Firmware, Edge ML Platform, Mobile, Cloud, and Connectivity teams.

You will ensure numerical equivalence, profile performance on device, and build reusable tools to accelerate future migrations, balancing compute, memory, latency