Founding ML Research Engineer

Description

About the Role

Join an early-stage industrial AI team building the multimodal AI core for wearable assistants used in field operations. You will own production vision-language systems end to end, from model orchestration and evaluation to deployment on real devices.

Responsibilities

• Build and ship agentic vision-language pipelines that support visual reasoning and multi-step workflows.
• Develop evaluation tools, capture failure modes, and create data and fine-tuning loops that improve model quality.
• Adapt model serving to field connectivity, latency constraints, and edge hardware, including graceful fallbacks.
• Create real-time voice and video interfaces, including conversational and proactive assistance modes.
• Fine-tune open-source multimodal models for enterprise deployment, using approaches such as SFT, RLHF, and quantization.

Requirements

• Typically 2 to 6 years of experience building and shipping production VLM or multimodal AI systems, using Python and PyTorch.
• Evidence of owning AI product outcomes, including agent loops with real tool use, model orchestration, evaluation, and data improvement workflows.
• Applied experience fine-tuning and deploying models, rather than a focus solely on pretraining from scratch.
• Experience with production vision-language systems, computer vision, and image or video reasoning; wearable, AR, industrial AI, or autonomous systems experience is valuable.
• Familiarity with serving and optimizing models using tools such as vLLM, Triton, Ray Serve, ONNX, TensorRT, Hugging Face Transformers, and quantization methods.
• A CS, machine learning, or engineering degree and a record of independently driving product work are preferred.

Conditions

Base salary: $180,000 to $230,000 annually. Visa sponsorship is available.

On-site in San Francisco, United States.