Senior Applied Machine Learning Engineer
Role summary
This hybrid role in the Bay Area is for a Senior Machine Learning Engineer specializing in Edge AI. The company is building technology that runs intelligence on devices in real-time. The engineer will design, train, and optimize deep learning models for computer vision, audio/speech, and sensor processing, then quantize, prune, and compress them for inference on constrained hardware like NPUs, DSPs, and microcontrollers. Responsibilities include building scalable training and evaluation pipelines, benchmarking architectures, collaborating with embedded software engineers for production integration, and owning the full ML lifecycle from data curation to documentation. A minimum of 3 years of experience in developing and deploying ML models in production is required, along with strong Python skills and familiarity with ML frameworks and edge AI compilers.
Senior Machine Learning Engineer (Edge AI)
Up to $200,000 pa
Hybrid - Bay Area
Most ML roles ask you to pick a lane and stay in it. This one doesn't.
We're working with a fast-moving embedded AI company building technology that runs intelligence at the edge. On the device, in real time, in the real world. One week you might be squeezing a computer vision model onto a microcontroller. Next, you're working on wake-word detection or multimodal sensor fusion. The work is genuinely varied, technically demanding, and shipping to production, not a research lab shelf.
What you'll be doing
- Design, train, and optimise deep learning models across computer vision, audio/speech, and sensor signal processing
- Quantise, prune, and compress models for real-time inference on NPUs, DSPs, and microcontrollers
- Build scalable training and evaluation pipelines and benchmark new architectures for edge deployment
- Collaborate directly with embedded software engineers to integrate models into production environments
- Own the full loop: data curation, training, error analysis, iteration, and documentation
What we're looking for
- 3+ years of hands-on experience developing and deploying ML models in production
- Strong Python skills and fluency with PyTorch, TensorFlow, ONNX, OpenCV, or equivalent
- Demonstrated experience with model quantisation, compression, and deployment on constrained hardware
- Familiarity with edge AI compilers - ARM Ethos-U/Vela, TensorRT, TFLite, or similar
- Solid understanding of signal processing across image, audio, and sensor modalities
- Degree in CS, ML, or related field - or an equivalent portfolio of deployed models that speaks for itself
Sound like the kind of role you've been waiting for? Take the next step in your career and apply today!
*5V Tech are acting as an Employment Agency for the purposes of this job vacancy. We offer a reward scheme if you can recommend someone for this position, up to $250 for you and an additional $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.*
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