Machine Learning Engineer – Edge AI / Computer Vision
- San Francisco, Bay Area (Hybrid – 3 days onsite)
- Full-Time Permanent
- Salary: $140,000–$200,000 (DOE)
- Total Comp: Equity, Bonus, Medical, Dental, Vision, 401(k) and more
A specialist embedded AI and intelligent systems company based in the Bay Area focuses on deploying production-grade AI into real-world, low-power, and constrained hardware environments. Working closely with semiconductor and hardware ecosystems, they help companies bring Edge AI to market across computer vision, robotics, industrial AI, healthcare devices, and smart infrastructure.
As part of their growth, they are expanding the engineering team behind their proprietary Edge AI development and deployment platform, a system that accelerates the journey from prototype to production via optimised models, deployment blueprints, benchmarking tools, and hardware integration workflows across embedded CPUs, GPUs, and NPUs.
They are now looking for an experienced Machine Learning Engineer to help build and optimise real-time computer vision, audio, and perception systems for deployment on constrained edge hardware.
Key Responsibilities:
- Deploy and optimise computer vision and audio AI models for real-time edge inference on embedded hardware
- Apply quantization (QAT/PTQ), model compression, and latency optimisation using TensorRT, TFLite, and ONNX Runtime
- Build and maintain object detection, segmentation, and perception pipelines for sensor-driven systems
- Develop and optimise audio and signal processing algorithms for on-device deployment
- Work with multi-sensor data including cameras, microphones, IMU, ToF, and other real-world inputs
- Contribute to deployment blueprints, benchmarking tools, and hardware integration workflows on the internal platform
- Collaborate across robotics, industrial, and healthcare sectors to deliver tailored production solutions
Ideal Profile:
- 3–5 years of hands-on experience in edge AI, embedded vision, or CV deployment engineering
- Proven experience optimising and deploying models using TensorRT, TFLite, or ONNX Runtime
- Strong understanding of quantization, model compression, and real-time inference constraints
- Experience with object detection or segmentation frameworks such as YOLO or OpenCV
- Experience with audio AI, DSP, or signal processing for on-device applications is a strong plus
- Background in robotics, autonomous systems, AV perception, or embedded vision strongly preferred
- Degree in Computer Science, Electrical Engineering, or related field (BS, MS, PhD or equivalent)
- Systems-level thinker who works close to hardware and understands real-world deployment tradeoffs
This is a rare opportunity to join a specialist embedded AI company at the forefront of on-device intelligence — contributing directly to a platform that is redefining how AI is built and deployed at the edge across vision, audio, and sensing.
APPLY NOW to discuss further details.
5V Tech are acting as an Employment Agency for the purposes of this position. We offer a reward scheme if you can recommend someone for this role — $250 for you and $250 to a charity of your choice. 5V Tech are recognised talent solutions experts within IoT and Deep Tech, working across Europe, the UK, and North America.
