Senior ML Research Engineer, Manipulation

RoboForce

$130K — $180K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Master's degree in Machine Learning, Robotics, or related field with 4+ years of experience or a PhD degree
  • Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX)
  • Understanding of multimodal models and modern ML architectures
  • Expertise in imitation learning, reinforcement learning, tactile sensing, and robotics learning
  • Experience with physical simulators (e.g., MuJoCo, IsaacSim) and deployed robotics environments
  • In-office collaboration required 5 days a week

Responsibilities

  • Design and deploy manipulation algorithms for high-DOF robotic tasks
  • Develop motion planning models for dynamic environments
  • Deploy models as production-ready solutions on RoboForce robots
  • Create and enhance contact-rich robot learning stacks through physics-based simulation

Benefits

  • Collaborative in-office work environment
  • Opportunity to advance and innovate within the robotics field
  • Chance to contribute to cutting-edge robotics technology
  • Potential for publication in top-tier robotics conferences
Full Job Description
We are looking for a Senior Research Engineer to advance robotic manipulation capabilities, enabling dynamic and physically interactive tasks. You will develop algorithms for grasping, motion planning, and tactile learning in real-world environments.

Responsibilities:
  • Design and deploy manipulation algorithms for high-DOF robotic tasks (e.g., grasping, connecting, picking, placing, etc).
  • Develop motion planning models for dynamic environments.
  • Deploy models as production-ready solutions on RoboForce robots.
  • Create and enhance contact-rich robot learning stacks through physics-based simulation.

Qualifications:
  • Master's degree in Machine Learning, Robotics, or related field with 4+ years of experience or a PhD degree.
  • Proficiency in Python, and deep learning frameworks (e.g., PyTorch, JAX).
  • Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.).
  • Expertise in imitation learning, reinforcement learning, tactile sensing and robotics learning.
  • Proficiency with one or more physical simulators (e.g., MuJoCo, IsaacSim, Drake, PyBullet, PhysX) and experience working in a deployed robotics environment.
  • Requires 5 days/week in-office collaboration with the teams.

Preferred Skills:
  • Strong publication on top conferences in robotics manipulation.
  • Expertise in neural network deployment (e.g., TensorRT) and GPU programming with CUDA.
  • Proven ability to design scalable experimentation and data pipelines.
  • Familiarity with 3D computer vision and/or graphics pipelines
  • Experience with Large Language Model.
  • Expertise in C++ programming.

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