Founding ML Researcher
True Talent Solutions Partners
17 hours ago
Full-time
On-site
About the Role
Join the founding engineering team at an early-stage industrial wearable AI startup. You will build and ship applied multimodal AI for smart glasses, helping field technicians work through complex operational tasks with real-time assistance.
What You'll Do
Build production agentic vision-language model pipelines that use multi-step reasoning and tools to support industrial workflows such as inspections and standard operating procedures.
Develop evaluation frameworks, capture failure cases, and create data and fine-tuning loops that improve model quality with each release.
Adapt model orchestration and edge inference to varying connectivity, latency, and hardware constraints, including graceful fallbacks.
Create real-time voice and video interfaces with conversational and proactive assistance modes.
Fine-tune open-weight multimodal models using methods such as supervised fine-tuning and RLHF, and prepare them for on-premise deployments.
What We're Looking For
Zero to three years of experience building and shipping production vision-language or multimodal AI systems, with end-to-end ownership of models and orchestration.
Strong Python and PyTorch skills, plus experience with agent tool-use loops, evaluation design, and data flywheels.
Applied experience with model fine-tuning, vision-language reasoning, and production deployment. This role is focused on shipped systems, not pretraining alone.
Familiarity with serving and optimization tools such as vLLM, Triton, Ray Serve, ONNX, TensorRT, quantization, or edge AI.
Startup or high-intensity engineering experience, and a degree in computer science, machine learning, or engineering, or equivalent demonstrated experience.
Interest or experience in computer vision, wearables, industrial AI, augmented reality, or autonomous systems. Graduate-level vision or multimodal research is a plus.
Compensation & Benefits
Salary range: $180,000 to $230,000 USD annually. Visa sponsorship is available.
Location
On-site in San Francisco, United States.
Join the founding engineering team at an early-stage industrial wearable AI startup. You will build and ship applied multimodal AI for smart glasses, helping field technicians work through complex operational tasks with real-time assistance.
What You'll Do
Build production agentic vision-language model pipelines that use multi-step reasoning and tools to support industrial workflows such as inspections and standard operating procedures.
Develop evaluation frameworks, capture failure cases, and create data and fine-tuning loops that improve model quality with each release.
Adapt model orchestration and edge inference to varying connectivity, latency, and hardware constraints, including graceful fallbacks.
Create real-time voice and video interfaces with conversational and proactive assistance modes.
Fine-tune open-weight multimodal models using methods such as supervised fine-tuning and RLHF, and prepare them for on-premise deployments.
What We're Looking For
Zero to three years of experience building and shipping production vision-language or multimodal AI systems, with end-to-end ownership of models and orchestration.
Strong Python and PyTorch skills, plus experience with agent tool-use loops, evaluation design, and data flywheels.
Applied experience with model fine-tuning, vision-language reasoning, and production deployment. This role is focused on shipped systems, not pretraining alone.
Familiarity with serving and optimization tools such as vLLM, Triton, Ray Serve, ONNX, TensorRT, quantization, or edge AI.
Startup or high-intensity engineering experience, and a degree in computer science, machine learning, or engineering, or equivalent demonstrated experience.
Interest or experience in computer vision, wearables, industrial AI, augmented reality, or autonomous systems. Graduate-level vision or multimodal research is a plus.
Compensation & Benefits
Salary range: $180,000 to $230,000 USD annually. Visa sponsorship is available.
Location
On-site in San Francisco, United States.