LandOfferFounding Machine Learning Engineer
About this role
Employer-provided description, formatted for easier reading.
San Francisco, CA · On-site · Full-time
Compensation: $180,000–$230,000 + 0. 25–0. 75% equity
About the Company
Our client is an early-stage, venture-backed startup building wearable AI assistants for industrial field workers: smart glasses powered by agentic vision-language models. Their product is deployed in critical-infrastructure and heavy-industry settings where AI has rarely been applied, and they are already working with anchor enterprise customers alongside a strong pipeline of large enterprise prospects.
Recently founded · Founding team stage · Industry: AI, Hardware, Robotics, Enterprise, B2B
The Role
Our client is hiring a founding machine learning engineer to own the AI core of their product from day one. You will build and ship multimodal systems that run on real hardware in the field, working directly with the founding team in a fast-moving, in-person environment. This role suits a hands-on builder who has put vision-language or multimodal systems in front of real users.
What you'll be doing
Building a production pipeline of multi-step, tool-using visual reasoning agents that run on smart glasses against real industrial workflows such as inspections and standard operating procedures
Creating real-time voice and video AI interfaces for the glasses, including conversational and proactive alert modes tailored to different users
Owning evaluation and the data flywheel: eval harnesses, capturing failure modes, and turning customer data into fine-tuning loops that improve model quality release over release
Delivering edge inference and model orchestration that adapts gracefully to changing connectivity and latency constraints in the field
Fine-tuning and optimizing open-source multimodal models (SFT, RLHF, quantization) for on-premise enterprise deployments
Tech stack: Python, PyTorch, vLLM, Triton, Ray Serve, ONNX, TensorRT, Hugging Face Transformers, LangChain, RAG, RLHF, SFT, quantization (GPTQ, AWQ), edge AI, multimodal LLMs, vision-language model...
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