Scale AI

2 months ago

Technical Lead Manager, Physical AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Lead a high-performance Research Engineer team at Scale’s Physical AI unit, bridging cutting-edge ML research with real-world robot deployment. You’ll hands-on code ~60% time while scaling large-scale foundation models (VLAs, world models), shaping data pipelines, and collaborating with customers to push Scale data-driven AI for embodied tasks.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Direct research into scaling laws for Physical AI and determine how to leverage large datasets for pre-training and fine-tuning generalist policies.
•Develop and evaluate VLA and World models, including creating new Physical AI industry benchmarks.
•Actively write code to implement, train and test state-of-the-art architectures and conduct research on data collection, cross-embodiment training, and policy fine-tuning.
•Collaborate with labeling teams to design robotic-native data pipelines, including use of vision-language models for trajectory annotation and data synthesis.
•Mentor and grow a team of 4-6 elite Physical AI researchers, and translate research into production-ready features for Scale’s partners.

Pay and Benefits

Salary: USD 248,800 - 311,000 annually

Perks:Health InsuranceDentalVisionRetirement BenefitsLearning BudgetPaid LeaveCommuter Benefits

Key Requirements

•Deep Learning Mastery with expert-level PyTorch, transformer architectures, attention mechanisms, and self-supervised learning.
•Proven track record with Vision-Language Models (e.g., CLIP, PaLM-E) and adapting them for spatial reasoning or embodied tasks.
•Experience with Generative AI (diffusion models or generative world models) for sequence generation or predictive modeling.
•Strong embodied AI background: imitation learning, reinforcement learning, and multi-modal sensor fusion; capable of distributed training across GPU clusters.
•1+ years of experience leading technical teams or projects in a research-intensive environment.

Experience:RoboticsAiMachine learning

Skills:LeadershipMentorshipCollaborationCommunicationProblem-solving

Languages:English

Tech Stack:PyTorchTransformerAttentionSelf-Supervised LearningCLIPPaLM-EDiffusion ModelsVision-Language ModelsImitation learningReinforcement learningDistributed trainingGPU clusters

Company Brief

Scale AI

Provides data labeling, annotation, and infrastructure services to accelerate machine learning and AI development. Supplies high-quality training data, tooling, and APIs for customers in autonomous vehicles, mapping, robotics, and enterprise AI applications.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2016

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Scale AI

2 months ago

Technical Lead Manager, Physical AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Direct research into scaling laws for Physical AI and determine how to leverage large datasets for pre-training and fine-tuning generalist policies.
•Develop and evaluate VLA and World models, including creating new Physical AI industry benchmarks.
•Actively write code to implement, train and test state-of-the-art architectures and conduct research on data collection, cross-embodiment training, and policy fine-tuning.
•Collaborate with labeling teams to design robotic-native data pipelines, including use of vision-language models for trajectory annotation and data synthesis.
•Mentor and grow a team of 4-6 elite Physical AI researchers, and translate research into production-ready features for Scale’s partners.

Pay and Benefits

Salary: USD 248,800 - 311,000 annually

Perks:Health InsuranceDentalVisionRetirement BenefitsLearning BudgetPaid LeaveCommuter Benefits

Key Requirements

•Deep Learning Mastery with expert-level PyTorch, transformer architectures, attention mechanisms, and self-supervised learning.
•Proven track record with Vision-Language Models (e.g., CLIP, PaLM-E) and adapting them for spatial reasoning or embodied tasks.
•Experience with Generative AI (diffusion models or generative world models) for sequence generation or predictive modeling.
•Strong embodied AI background: imitation learning, reinforcement learning, and multi-modal sensor fusion; capable of distributed training across GPU clusters.
•1+ years of experience leading technical teams or projects in a research-intensive environment.

Experience:RoboticsAiMachine learning

Skills:LeadershipMentorshipCollaborationCommunicationProblem-solving

Languages:English

Tech Stack:PyTorchTransformerAttentionSelf-Supervised LearningCLIPPaLM-EDiffusion ModelsVision-Language ModelsImitation learningReinforcement learningDistributed trainingGPU clusters

Company Brief

Scale AI

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2016

Website LinkedIn