Technical Lead, Multimodal Research
$150k - $300k • San Francisco • FullTime
Posted 23d ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Eventual is building data curation for Physical AI, processing petabyte-scale video and sensor data to extract signals about how hands and objects interact, temporal events, and clip reliability for training frontier models. We are a small, well-backed team from leading tech companies, aiming to revolutionize how Physical AI models are trained by providing reliable, curated datasets derived from vast amounts of video footage. This role is based in our SF Mission District office, with a 4-day work week.
As Technical Lead, Multimodal Research, you will drive the technical vision for Eventual's understanding of video data. You will own the strategy for selecting, prototyping, and deploying models and representations at scale, ensuring they meet rigorous evaluation standards and cost-efficiency targets. This is a senior individual contributor role focused on setting research direction and making key architectural decisions, while remaining hands-on with research and experimentation.
Responsibilities
- Own modeling strategy across the platform, including model families, representations, and training approaches.
- Transition approaches from prototype to production inference at corpus scale, collaborating with data systems and storage teams.
- Define evaluation standards and acceptance criteria for models.
- Manage the cost of data understanding through architectural decisions like distillation, cascades, routing, and quantization.
- Translate customer research needs into scoped technical programs and set technical direction for multimodal work.
Requirements
- 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, or equivalent publication/production record.
- Deep understanding of modern vision and multimodal modeling (VLMs, VQA, embeddings, representation learning, detection, tracking, segmentation, retrieval) with a focus on deployable solutions.
- Hands-on experience training and evaluating models at scale on real video and sensor data.
- Proficiency in both PyTorch prototyping and production inference performance, GPU utilization, throughput, and cost.
- Background from a perception or multimodal team at a self-driving, robotics, or Physical AI company, a frontier research lab, or a visual-data company, ideally as the senior-most person on a problem.
Benefits
- 4 days/week in SF Mission office
- Competitive compensation
- Meaningful startup equity
- Catered lunches and dinners
- Commuter benefit
- Team-building events
- Health, vision, and dental coverage
- Flexible PTO
- Latest Apple equipment
- 401(k) plan with match