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Machine Learning Engineer Intern, AI & Robotics

RoboForce

Skills

Required

  • Robotics
  • Machine Learning
  • reinforcement learning
  • multimodal models
  • modern machine learning architectures
  • transformers and diffusion models
  • PyTorch / JAX / TensorFlow

Preferred

  • robot learning
  • object pose estimation
  • bimanual manipulation
  • synthetic data
  • simulation
  • labeling

Machine Learning Engineer Intern

About RoboForce

Why RoboForce

RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company’s robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.

Responsibilities

  • to join us in developing advanced AI capabilities for robotics. The internship starts from November 2026 for 3-6 months. As part of our team, you will help build the foundational AI ecosystem, spanning
  • data collection, labeling, training, evaluation, and deployment.
  • You will collaborate closely with a team of world-class AI engineers and gain hands-on experience solving real-world challenges at the intersection of artificial intelligence and robotics.
  • Train and improve robot foundation models, including vision-language-action (VLA) models and world-action models, for precise, contact-rich manipulation in industrial settings.
  • Explore new modalities and methods, including tactile and force-torque sensing, reinforcement learning, and simulation, to advance model capabilities.
  • Build data pipelines for robot learning, including data collection, curation, labeling, and dataset quality assurance.
  • Design and run evaluations in simulation and on real robots to measure and improve model performance.
  • Deploy models on robots and optimize them for real-time onboard inference.
  • Work closely with robotics, hardware, and product teams to bring models from research to production.

Requirements

  • Currently pursuing an advanced degree in Computer Science, Robotics, Machine Learning, or a related field, with a graduation date in 2026 or 2027.
  • Proficiency in multimodal models, modern machine learning architectures (e.g., transformers and diffusion models), and reinforcement learning.
  • Proficiency in deep learning frameworks such as PyTorch, JAX, or TensorFlow.
  • Requires 5 days/week in-office collaboration with the teams.
  • 3–6 months, full-time

Preferred

  • Exposure to robot learning using tactile and/or vision-based sensors.
  • Expertise in object pose estimation, bimanual manipulation, and synthetic data.

Pay

$5,000 - $6,500 monthly salary