Staff Machine Learning Engineer - Action Models
CloudKitchens5 days ago
Base Salary
$273k - $321k/yr
Responsibilities
- Define and help build the technical architecture for action models and learned decision-making systems.
- Develop models that translate learned representations of the physical world into decisions, plans, and actions.
- Research architectures for reasoning, planning, control, action generation, learned policies, and action heads in robotics and autonomous systems.
- Develop approaches connecting perception and world models to downstream decision-making and control.
- Research imitation learning, reinforcement learning, behavior learning, and other data-driven decision-making methods.
- Explore vision-language-action and other multimodal architectures for physical AI.
- Train and evaluate models using large-scale real-world, simulated, and synthetic data.
- Develop methods for learning from demonstrations, human behavior, robot experience, and other supervision sources.
- Make architectural decisions across data, model design, training, evaluation, inference, and deployment.
- Establish evaluation methods for reasoning, planning, action quality, robustness, and generalization.
- Translate embodied-intelligence research into reliable systems for real machines.
- Provide technical leadership through research direction, architecture reviews, mentorship, experimentation, hands-on engineering, and talent assessment.
Requirements
- Deep expertise in machine learning applied to decision-making, robotics, autonomous systems, or embodied intelligence.
- Strong understanding of modern deep learning architectures and sequential decision-making in physical systems.
- Experience with reinforcement learning, imitation learning, behavior learning, planning, control, robot learning, or embodied AI.
- Experience connecting learned representations or perception to downstream actions.
- Strong understanding of sequential and temporal modeling and how actions influence future states.
- Experience training and evaluating models with large-scale real-world, simulated, or synthetic datasets.
- Strong understanding of the full ML lifecycle, including data strategy, model architecture, training, evaluation, optimization, and inference.
- Experience translating research ideas into functioning machine learning systems.
- Strong software engineering fundamentals and hands-on ability in Python and/or C++.
- Track record of consequential technical decisions and influence beyond an individual project.
- Ability to work in ambiguous research spaces and communicate complex technical ideas across research, engineering, and robotics disciplines.
Benefits
- Medical, dental, vision, disability, and life insurance.
- Flexible Spending Account and Health Savings Account options.
- 401(k) and equity eligibility.
- Sick time, unlimited flexible time off, and paid holidays.
- Paid parental leave.
- Pre-tax commuter benefit plan.
- Team lunch in the SoMa office every Tuesday and Thursday.
- Based in San Francisco and onsite five days per week for office-based teams.
Categories
ML EngineeringRobotics
About CloudKitchens
CloudKitchens builds delivery-first commercial kitchen facilities and restaurant software for food and beverage operators. It leases turnkey kitchen space and provides tools for order management, delivery logistics, and multi-brand operations, enabling restaurants and entrepreneurs to expand with lower upfront costs. The company is privately held and headquartered in Los Angeles, serving markets across the U.S. with a mix of owned sites and enterprise solutions.