Chief Staff Applied Scientist

hace 2 días

Desde casa, México EPAM Systems, Inc. A tiempo completo

We are seeking a Chief Applied Scientist to spearhead the advancement of robotic policies for dexterous manipulation in practical environments.

In this leadership role, you will oversee the creation, training, and rollout of sophisticated robot learning models that merge multimodal perception, policy learning, and physical execution. Join a dynamic team dedicated to pushing the limits of embodied AI and addressing large-scale industrial autonomy and simulation challenges. Apply now to lead innovation in robotics and AI.

Responsibilities

  • Design and deploy cutting-edge robot learning models and policy architectures for manipulation and autonomous task sequencing, incorporating multimodal sensory inputs, perception, planning, and execution on robotic platforms with ROS/ROS2
  • Develop and refine comprehensive policy training pipelines, including policy inference and closed-loop control systems, tailored for both real and simulated settings
  • Lead the data strategy for demonstrations, teleoperation, simulation workflows, and evaluation frameworks to facilitate reliable, safe, and repeatable robot policy implementations
  • Collaborate with multidisciplinary teams and AI infrastructure specialists to launch scalable, production-grade robotics solutions
  • Monitor the latest embodied AI research, contribute to reproducible studies, and disseminate knowledge via mentorship and technical talks
  • Enhance PyTorch implementations through custom module development and performance optimization to ensure efficient model deployment

Requirements

  • Doctorate in a relevant STEM discipline or Master's degree with equivalent industry experience in robotics or embodied AI
  • Minimum of 7 years experience developing and deploying machine learning models on robotic platforms, integrating multimodal sensory data with control outputs
  • In-depth understanding of contemporary AI architectures such as Transformers, diffusion models, and VLM/VLAs
  • Proficient in PyTorch with experience creating custom modules and optimizing model performance
  • Hands-on experience with Robot Operating System (ROS/ROS2) and integrating policies within robotic systems
  • Demonstrated impact through scholarly publications, open-source projects, or production system deployments
  • Capability to lead intricate projects involving collaboration across various teams
  • Excellent problem-solving, analytical abilities, and communication skills with English proficiency at C2 level

Nice to have

  • Expertise in computer vision related to 3D data, including perception and affordance modeling
  • Knowledge of simulation tools like Isaac Sim, Mujoco, Gazebo, or PyBullet
  • Proficiency in dexterous manipulation and executing multi-step autonomous tasks
  • Awareness of visual trends and their application to embodied AI challenges
  • Experience in customizing foundation models for embodied control and instruction-following agents

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