Quick overview
Job description
About the Role
Join an early-stage industrial AI team building wearable AI copilots for field workers. You will own core parts of the multimodal AI stack, from production vision-language systems to real-time experiences running on hardware in the field.
What You'll Do
Build and ship agentic vision-language pipelines for smart glasses, including multi-step visual reasoning and tool use in industrial workflows.
Develop evaluation harnesses, capture failure modes, and turn customer data into fine-tuning cycles that improve model quality.
Adapt model orchestration and edge inference to variable 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.
End-to-end ownership of production AI products, including model orchestration, evaluation, and downstream product outcomes.
Experience building multi-step agents with real tool use, rather than only retrieval wrappers or single-turn chatbots.
Applied expertise in fine-tuning methods such as SFT and RLHF, evaluation design, and visual reasoning; pretraining from scratch is not the focus.
Familiarity with technologies such as vLLM, Triton, Ray Serve, ONNX, TensorRT, Hugging Face Transformers, quantization, and edge inference.
Startup, founding-engineer, or other high-ownership product-building experience, and a strong interest in computer vision, wearables, and industrial AI.
A bachelor's or master's degree in computer science, machine learning, or engineering, or equivalent practical experience.
Production wearable or AR AI, autonomous-driving vision, on-premise deployment, or constrained-hardware experience is valuable.
Compensation & Benefits
Base salary: $180,000 to $230,000 annually. Visa sponsorship is available.
Location
On-site, five days per week in San Francisco, California.