Technical Lead Manager (Physical AI)

TL;DR

Technical Lead Manager (Physical AI): Leading a team of Research Engineers to build general AI that can reason and act in the physical world with an accent on Large-Scale Foundation Models (VLAs, World models). Focus on scaling laws for Physical AI, cross-embodiment training, and translating SOTA research into production-ready features.

Location: San Francisco, CA

Salary: $248,800 - $311,000 USD

Company

Scale AI is the data engine for the entire AI industry, providing high-quality data infrastructure to help frontier labs build Foundation Models for Physical AI.

What you will do

• Lead and grow a team of 4-6 elite Physical AI researchers, fostering a culture of high-velocity experimentation.
• Direct research into scaling laws for Physical AI to optimize pre-training and fine-tuning of generalist policies.
• Develop and evaluate novel VLA and World models, including the creation of new industry benchmarks.
• Actively implement, train, and test SOTA architectures with a focus on cross-embodiment training.
• Design robotic-native data pipelines using VLMs for automated trajectory annotation and data synthesis.
• Translate research from top-tier conferences (NeurIPS, ICRA, CVPR) into production-ready features.

Requirements

• Expert-level proficiency in PyTorch, Transformer architectures, Attention mechanisms, and Self-Supervised Learning.
• Proven track record with Vision-Language Models (e.g., CLIP, PaLM-E) adapted for spatial reasoning or embodied tasks.
• Experience with Diffusion Models for sequence generation or Generative World Models.
• Strong understanding of the Physical AI stack, including imitation learning, RL, and multi-modal sensor fusion.
• Experience with large-scale distributed training across GPU clusters and high-performance data loading.
• 1+ years of experience leading technical teams in a research-intensive environment.
• Must be based in San Francisco, CA

Nice to have

• First-author publications at top-tier AI/ML conferences (NeurIPS, CVPR, ICRA, CoRL).
• Experience building models that generalize across different robot morphologies (arms, humanoids, mobile bases).
• Experience with high-fidelity simulators such as Isaac Gym or MuJoCo.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Equity compensation and retirement benefits.
• Learning and development stipend.
• Generous PTO and commuter stipend.