Technical Lead Manager, Physical AI
Role Overview
The Technical Lead Manager (TLM) for the Physical AI team of Scale will bridge the gap between cutting-edge Machine Learning research and physical robot deployment. They will lead a high-performing team of Research Engineers while remaining a hands-on technical contributor.
Key Responsibilities
Technical Leadership & Research: Direct research into scaling laws for Physical AI, determine how to best utilize massive datasets for pre-training and fine-tuning generalist policies.
VLA and World model development: Develop novel methods for developing and evaluating models, including new Physical AI industry benchmarks.
Hands-on Modeling: Actively write code to implement, train and test state-of-the-art architectures. Conduct research on Physical AI data collection, cross-embodiment training, and policy fine-tuning.
Data Strategy: Collaborate with internal labeling teams to design "robotic-native" data pipelines, including the use of VLMs for automated trajectory annotation and data synthesis.
Collaborate closely with customers to drive the industry forward in using Scale data.
Team Management & Execution
Mentorship: Lead and grow a team of 4-6 elite Physical AI researchers, fostering a culture of high-velocity experimentation and rigorous evaluation.
Paper-to-Product: Translate the latest research from NeurIPS, ICRA, and CVPR into production-ready features for Scale’s Physical AI partners.
Cross-functional Alignment: Work with cross-functional teams (e.g. Product and Operations) to bring our research breakthroughs into production.
Required Qualifications
AI/ML Excellence: Deep Learning Mastery: Expert-level proficiency in PyTorch, with deep knowledge of Transformer architectures, Attention mechanisms, and Self-Supervised Learning.
VLM/VLA Experience: Proven track record of working with Vision-Language Models (e.g., CLIP, PaLM-E) and adapting them for spatial reasoning or embodied tasks.
Generative AI: Experience with Diffusion Models for sequence generation or Generative World Models for predictive modeling.
Physical AI & Software Background: Strong understanding of Physical AI stack, including imitation learning, reinforcement learning (RL), and multi-modal sensor fusion.
Infrastructure: Experience with large-scale distributed training across GPU clusters and high-performance data loading.
Leadership: 1+ years of experience leading technical teams or projects in a research-intensive environment.
Nice to Haves
Publication Record: First-author publications at top-tier AI/ML conferences (NeurIPS, CVPR, ICRA, CoRL).
Hardware Generalization: Experience building models that work across different robot types (arms, mobile bases, humanoids).
Sim-to-Real: Experience with high-fidelity simulators (e.g., Isaac Gym, MuJoCo) and the nuances of physical domain adaptation.
Compensation
Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
About Us
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities.