Founding ML Research Engineer

About the Role

Join an early-stage industrial AI team building wearable AI copilots for field technicians in critical infrastructure. You will own key parts of the multimodal stack, from production vision-language systems and evaluation to edge inference and real-time voice and video experiences.

What You'll Do

• Build and ship agentic vision-language pipelines for smart glasses, including visual reasoning and tool use across real industrial workflows.

• Develop evaluation systems, capture failure cases, and create data and fine-tuning workflows that improve model quality over time.

• Adapt model orchestration and edge inference to changing connectivity, latency, and hardware constraints.

• Create real-time voice and video interfaces, including conversational and proactive alert experiences.

• Fine-tune and optimize open-weight multimodal models for enterprise and on-premise deployments.

What We're Looking For

• Two to six years of experience shipping production vision-language or multimodal AI systems, using Python and PyTorch.

• Experience owning model and orchestration layers, delivering end-user products, and taking responsibility for product outcomes.

• Hands-on work with multi-step agents and tool use, evaluation design, data flywheels, and fine-tuning methods such as SFT or RLHF.

• Strong applied computer vision and vision-language experience, with production deployment beyond research or pretraining alone.

• Startup, founding-engineer, or similarly high-ownership experience, plus a track record of driving greenfield work independently.

• A relevant bachelor's or master's degree, or equivalent engineering experience; experience with wearables, AR, autonomous systems, edge inference, or on-premise serving is valuable.

• Familiarity with tools such as vLLM, Triton, Ray Serve, ONNX, TensorRT, Hugging Face Transformers, and model quantization.

Compensation & Benefits

Base salary is $180,000 to $230,000 annually. Visa sponsorship is available. Equity details were not provided.

Location

On-site, five days per week in San Francisco, California, United States.