Physical AI R&D Scientist

EY•Palo Alto, CA

7d•$116,700 - $198,300•Onsite

About The Position

EY is scaling Physical AI capabilities in California (Palo Alto) to serve as a premier engagement hub for clients, industry leaders, startup founders, alliance partners, investors, and the broader innovation ecosystem. We are seeking a highly organized, client-centric, and operationally driven Assistant Director to technically drive the development and validation of various Physical AI and robotics showcases for EY.ai Labs (Palo Alto). The candidate will work closely with the Experience Lead- EY.ai Labs (Palo Alto) as well as collaborate with the Physical AI R&D team (based out of Alpharetta, Georgia), the EY Physical AI leadership, client account teams and alliance partners to build reusable accelerators and industry showcases. The role requires a combination of deep technical expertise, hands-on engineering capability, and the ability to communicate complex concepts to technical and executive audiences. The ideal candidate has experience developing robotic AI systems in simulation and on physical platforms and is comfortable operating in an applied R&D environment that focuses on measurable business outcome and client value.

Requirements

Strong hands-on experience in robotics, embodied AI, machine learning, computer vision, or autonomous systems research and development.
Demonstrated experience developing robotics applications using VLA models, World foundation models and/or other AI models.
Advanced proficiency in Python and working proficiency in C++ or another language commonly used in robotics systems along with experience designing, training, fine-tuning, and evaluating machine-learning models using frameworks such as PyTorch or equivalent technologies.
Hands-on experience with NVIDIA Omniverse, Isaac Sim, Isaac Lab, Cosmos, or comparable robotics simulation and synthetic-data platforms would be highly beneficial.
Deep experience with robotics development frameworks, preferably ROS or ROS 2, and with the integration of sensors, actuators, cameras, and robotic platforms.
Strong understanding of robotic perception, manipulation, navigation, motion planning, control, reinforcement learning, imitation learning, and sim-to-real transfer.
Strong understanding of safety, security, responsible AI, and risk considerations associated with AI-enabled physical systems is a must-have.
Ability to convert business and industry challenges into well-defined technical problems, research questions, experiments, and prototype architectures.
Strong communication and stakeholder management skills, including the ability to explain complex technical concepts to engineers, business leaders, clients, and ecosystem partners in high-visibility engagements into business relevant client experiences and engagement journeys.
Ability to operate effectively in a fast-paced, evolving and highly collaborative multidisciplinary environment involving engineering, business, alliance, and client stakeholders.
Strong organizational and execution skills with a proactive, problem-solving mindset.
High level understanding of emerging technologies including AI, robotics, automation, digital twins, simulation, and intelligent systems.

Nice To Haves

PhD in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a related discipline.
R&D experience in humanoid robotics or general-purpose robotic systems, including development of VLA-based robotic systems or multimodal foundation-model applications for planning, manipulation, navigation, or human-robot interaction.
Deep experience with NVIDIA Omniverse, Isaac Lab, Isaac Sim, Cosmos, and associated accelerated computing platforms would be a plus.
Strong Experience with synthetic data generation, reinforcement learning, imitation learning, teleoperation data, domain randomization, and sim-to-real transfer, deploying robotics or AI workloads on edge-computing systems and optimizing models for inference latency and resource constraints.
Deep familiarity with cloud-based machine-learning platforms (ex: AWS, Azure), MLOps practices, robotics data pipelines, and distributed training environments.
Strong knowledge of Agentic AI and its application in edge devices and robotic systems.
Experience collaborating with clients or industry teams to develop art-of-the-possible technical showcases.
Established network across the Bay Area robotics innovation communities, venture capital firms, startups, and technology ecosystems is a bonus.

Responsibilities

Design and develop intelligent robotic systems and reusable assets leveraging Vision-Language-Action models, Robot Foundation Models and related technologies.
Build, train, fine-tune, evaluate, and integrate the respective AI models that enable robotic perception, reasoning, planning, manipulation, navigation, and human-machine interaction.
Design workflows for synthetic data generation (using teleoperation, VR or other means), reinforcement learning, imitation learning, policy evaluation, and sim-to-real transfer.
Evaluate new robotic foundation models, simulation technologies, and development frameworks for potential inclusion in EY’s Physical AI portfolio.
Collaborate with EY.ai Labs (Alpharetta) R&D team, including extended technical teams as part of the lab network from other locations, to share code, datasets, models, and reusable assets.
Serve as the key technical lead by working alongside the Experience Lead for client workshops, executive briefings and innovation sessions.
Partner with client account teams and leaders to understand client challenges and business priorities and translate that into requirements which would help drive development roadmap.
Contribute to technical points of view, research papers, invention disclosures, reference architectures, internal learning materials, and external technical presentations, subject to EY IP and publication processes.
Mentor technical team members, while promoting strong engineering practices, reproducibility, responsible AI, and safe robotics development.
Support prioritization of the EY.ai Labs (Palo Alto) R&D roadmap in alignment with global roadmap, strategy, client demand, industry relevance, and commercialization priorities.
Develop simulation and digital-twin environments using NVIDIA Omniverse, Isaac Sim, Isaac Lab, Cosmos, or comparable platforms would be a huge plus.
Coordinate setup, testing, and readiness of technical showcases involving Physical AI technologies or assets prior to client engagements, as well as coordinate the customization of demonstrations, showcases, presentations, and experience journeys to ensure relevance and impact for each audience.
Support the rollout of new demonstrations, industry-specific showcases, and emerging Physical AI capabilities in alignment with EY commercialization priorities.