Technical Lead, Multimodal Research

What you'll do

• Choose modeling strategies and representations across the platform, and take promising approaches from prototype to production inference.
• Define model benchmarks and acceptance criteria, and make architecture decisions to control inference costs.
• Translate customer research needs into technical programs and set multimodal technical direction.

What they ask for

• 5+ years in applied computer vision or multimodal ML.
• PhD or MS in computer science, electrical engineering, robotics, or applied mathematics with a computer vision or machine learning focus; comparable publication or production record accepted instead.
• Depth in modern vision and multimodal modeling, including deployability judgment.
• Hands-on model training and evaluation at scale on real video and sensor data, with experience spanning research, engineering, inference performance, GPU utilization, throughput, and cost.

Nice to have

• Publications at CVPR, ICCV, ECCV, NeurIPS, ICML, or ICLR.
• Background on a perception or multimodal team at a self-driving, robotics, or Physical AI company, frontier research lab, or visual-data company; ideally the senior-most person on the problem.

Pay

$150K – $300K USD base salary

Tools

VLMs, VQA, embeddings, representation learning, detection, tracking, segmentation, PyTorch

AI focus

Develops and deploys vision and multimodal models to understand video and sensor data, curate training datasets, and evaluate model quality and cost at scale.