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About the Role
Join an early-stage industrial AI team building wearable AI copilots for field technicians working in critical infrastructure. You will own core parts of the multimodal AI stack, from production vision-language pipelines 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 multi-step visual reasoning and tool use in industrial workflows.
Develop evaluation frameworks, capture failure cases, and create customer-data fine-tuning loops to improve model quality over time.
Adapt field connectivity and edge inference through model orchestration, runtime optimization, and graceful fallbacks for varying latency and network conditions.
Create real-time voice and video interfaces, including conversational and proactive alert experiences tailored to end users.
Fine-tune and optimize multimodal models for enterprise and on-premise deployment.
What We're Looking For
Two to six years of experience shipping production vision-language or multimodal AI systems, with Python and PyTorch.
Experience owning model and orchestration layers end to end, and delivering AI products with measurable user outcomes.
Hands-on experience with multi-step agents that use tools, evaluation design, data feedback loops, and applied model fine-tuning such as SFT or RLHF.
Strong applied computer vision and vision-language model experience, rather than pretraining research alone.
Startup, founding-engineer, greenfield product, or similarly high-ownership experience, plus a CS, ML, or engineering degree.
Experience with edge or on-prem deployment is valuable, including vLLM, Triton, TensorRT, quantization, or constrained hardware; wearable, AR, or autonomous-driving experience is also relevant.
Genuine interest in computer vision, wearables, and industrial AI.
Compensation & Benefits
Base salary is $180,000 to $230,000 USD annually. Visa sponsorship is available.
Location
On-site, five days per week in San Francisco, California, United States.
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