Senior ML Engineer (AI Research, Physical AI)

About This Opportunity

We are representing a confidential AI cloud infrastructure organization in their search for a Senior ML Engineer to join their Physical AI research division. This is a remote opportunity focused on applied research in artificial intelligence, specifically building intelligent agents that can perceive, reason, and act in the physical world.

Our talent team at Get A Job.ai is working directly with this organization to identify exceptional candidates with deep expertise in robotics, reinforcement learning, and foundation models. You will be joining a team dedicated to advancing the state of the art in vision-language-action models, embodied AI, and general-purpose robotic control.

Responsibilities

In this role, you will modify large foundation models and learning algorithms for robotic agents, prototype new capabilities in simulation, and validate promising approaches on real-world systems. Your work will often lead to collaboration with adjacent research, infrastructure, and engineering teams.

Specific responsibilities may include:

• Designing, implementing, training, and evaluating large models and learning algorithms for robotic agents
• Developing vision-language-action architectures that connect multimodal perception and language understanding with physical control
• Investigating reinforcement learning and imitation learning methods for sparse, delayed, or difficult-to-verify objectives
• Building scalable methods for incorporating demonstrations, teleoperation data, video, simulation trajectories, and autonomous robot experience into foundation models
• Designing capture methodologies, datasets, evaluation protocols, and data-quality pipelines for embodied learning
• Developing simulation environments and conducting sim-to-real experiments on physical robotic platforms
• Exploring planning, guided generation, and search over action trajectories
• Prototyping new capabilities in areas such as dexterous manipulation, mobile manipulation, and whole-body control
• Writing robust research software and distributed training infrastructure that enable rapid experimentation
• Collaborating with research and engineering teams to translate promising ideas into reliable real-world systems
• Communicating results through technical reports, open-source releases, demonstrations, and research publications

What We're Looking For

Required qualifications:

• Profound understanding of the theoretical foundations of machine learning, reinforcement learning, or robot learning
• Deep expertise in at least one relevant area, such as reinforcement learning, imitation learning, multimodal generative modeling, computer vision, robotics, planning, or control
• Experience training and evaluating modern deep learning models, including transformer-based or multimodal foundation models
• Substantial experience training large models across multiple computational nodes
• Strong software engineering and algorithm-design skills; primary language is Python
• Deep experience with a modern deep learning framework; the team primarily uses JAX
• Experience designing, executing, and analyzing machine learning experiments with appropriate statistical rigor
• Ability to formulate meaningful research questions, design experiments that test clear hypotheses, and draw defensible conclusions
• Experience implementing research ideas and iterating quickly across modeling, data, infrastructure, and evaluation
• Strong communication and leadership abilities, including the ability to collaborate across research and engineering disciplines
• Ability to document research findings clearly and contribute to technical reports or research publications

Preferred qualifications:

• Experience working with real-world robots and robotic simulation environments
• Experience with dexterous manipulation, whole-arm manipulation, mobile manipulation, or humanoid robotics
• Experience with multimodal sensing, including tactile, force-torque, depth, and proprioceptive signals
• Experience collecting human demonstrations through teleoperation, motion capture, wearable devices, or observation
• Experience developing or post-training vision-language models, vision-language-action models, or video and world models
• Experience with deep reinforcement learning techniques such as offline RL, actor-critic methods, PPO, reward modeling, preference learning, or model-based RL
• Familiarity with robotics tools and simulators such as MuJoCo, Isaac Sim, Isaac Lab, PyBullet, ROS, or equivalent systems
• Knowledge of scalable training techniques such as FSDP or ZeRO, FlashAttention, mixed-precision training, quantization, and distributed checkpointing
• A PhD in Computer Science, Robotics, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience
• A track record of impactful publications, open-source contributions, or deployed robotic systems
• Experience engineering large distributed data-processing, simulation, or model-training systems
• A record of building and delivering products or research prototypes in a dynamic, startup-like environment
• Passion for moving research from controlled experiments to capable, reliable real-world robotic systems
• Excellent command of English, with strong technical writing, presentation, and communication skills
• Proficiency in contemporary software engineering practices, including version control, testing, code review, and CI/CD

How We Work With You

When you apply through Get A Job.ai, a member of our recruiting team will review your application and screen qualified candidates. We will then submit your profile to our client for consideration. Please do not contact the hiring organization directly—all communication should go through Get A Job.ai to ensure a smooth and professional process.

We provide personalized support throughout the interview process and will keep you informed at every stage.

Pay

Compensation details will be discussed with qualified candidates during the screening process.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applications from candidates of all backgrounds and provide equal opportunity regardless of race, color, religion, sex, national origin, age, disability, or any other protected characteristic.