Founding ML Researcher

About the Role

Join an early-stage team building wearable AI assistants for industrial field work. In this founding role, you will develop and ship applied vision-language systems that help technicians carry out real-time inspections and operational workflows.

What You'll Do

• Build production agentic vision-language pipelines for smart glasses, including multi-step visual reasoning and tool use for industrial procedures.

• Develop evaluation harnesses, capture model failure modes, and create data and fine-tuning loops that improve quality over time.

• Adapt model orchestration and inference to variable connectivity, latency limits, and edge hardware, with reliable fallback behavior.

• Create real-time voice and video interfaces, including conversational and proactive assistance modes for different users.

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

What We're Looking For

• 0 to 3 years of experience shipping production vision-language or multimodal AI systems, with end-to-end ownership of models and orchestration.

• Strong Python and PyTorch skills, plus hands-on experience with agent loops, tool use, evaluation design, and data flywheels.

• Applied fine-tuning experience, such as SFT or RLHF, and familiarity with model serving or optimization tools such as vLLM, Triton, TensorRT, ONNX, or quantization.

• Experience with visual reasoning and, where relevant, detection or segmentation. This role focuses on applied deployment rather than pretraining models from scratch.

• Startup, founding-engineer, or similarly high-ownership experience, and a strong interest in computer vision, wearables, or industrial AI.

• Edge inference, on-premise deployment, AR or wearable AI, or autonomous-driving vision experience is valuable.

• A bachelor's or master's degree in computer science, machine learning, or engineering, or equivalent applied experience.

Compensation & Benefits

Compensation is $180,000 to $230,000 annually. Visa sponsorship is available.

Location

This is an on-site role in San Francisco, California.