Senior Embedded Engineer, DSP Algorithms

Number of employees

120

San Francisco, CA, USA

Posted on: 2025-12-16

Category: energy

Apply now

Please let Gridware know you found this job on Work in Green. This will help us grow!

Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

About the company:

Gridware is a technology company focused on protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced active grid response platform uses high-precision mechanical sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is headquartered in San Francisco, California, and is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.

About Gridware
Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.

Role Description
We are looking for a highly skilled Embedded Engineer who can translate advanced DSP algorithms and machine learning models into efficient, production-ready C/C++ implementations optimized for extremely resource-constrained environments. You will work closely with ML scientists and firmware teams to bring cutting-edge signal processing capabilities onto embedded platforms with strict memory, computing and power budgets.

This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!

Benefits
Health, Dental & Vision (Gold and Platinum with some providers plans fully covered) 
Paid parental leave 
Alternating day off (every other Monday)
“Off the Grid”, a two week per year paid break for all employees. 
Commuter allowance 
Company-paid training 

Responsibilities

  • Convert DSP algorithms and build ML inference pipelines into efficient embeddedC/C++ code for microcontrollers or other constrained platforms.
  • Optimize code for memory footprint, CPU usage, and real-time performance.
  • Collaborate with algorithm / ML researchers to refine models for embedded deployment.
  • Profile runtime behavior, identify bottlenecks, and perform low-level debugging.
  • Work with firmware teams to integrate algorithms into system software.
  • Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health.
  • Required Skills

  • BS/MS in Electrical Engineering, Computer Engineering, Computer Science, or related field.
  • Strong proficiency in C/C++ for embedded systems.
  • Ability to read/translate algorithmic descriptions in Python/Matlab into low-level code.
  • Experience translating and optimizing machine learning models for embedded targets (e.g., quantization, fixed-point, pruning).
  • Understanding basic DSP concepts (filters, FFTs, spectral processing, etc.)
  • Familiarity with microcontrollers, RTOS, SoCs, or custom hardware.
  • Bonus Skills

  • Experience with ARM Cortex-M or similar MCUs.
  • Knowledge of low-level optimization techniques such as pipeline-aware coding, lookup table design, and memory layout optimization.
  • Hands-on experience with on-device ML frameworks (CMSIS-NN, etc.).
  • Experience in common ML frames (TensorFlow, PyTorch, Boosted Training, etc.)
  • Experience working in extreme resource-restricted systems.
  • Experience pushing on-device ML models to production (C++)
  • Similar climate jobs

    These are some of our top picks for great climate jobs on Work in Green.

    View all jobs

    91 Energy jobs at Gridware

    Gridware is hiring Senior Embedded Engineer, DSP Algorithms,Sr. Mechanical Engineering Manager,Senior Applied ML Scientist, ML DSP, and more.

    View all jobs at Gridware