Robotics ML Engineer: Post-Training Deployment

Skild; San Mateo (CA); On-site; USD 100,000 - 300,000; Full time

Job summary

Skild AI is seeking a Research Engineer to advance post-training and deployment of foundation models on real robots. You will improve models and deploy them in field environments, collaborating with customers to ensure reliable, safe robotic behavior.

As part of the post-training team, you will own data collection, build evaluation pipelines, and coordinate with robotics teams to enable on-site deployments across diverse tasks, scaling robust performance in real-world settings.

Qualifications

• BS, MS or PhD in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Deep knowledge in computer vision and deep learning for robotics, incl. reinforcement and imitation learning.
• Prior experience with large-scale model training.
• Prior experience deploying ML models or software on real robots.
• Prior experience with ROS/ROS2 or other robotics middleware.

Responsibilities

• Research, post-train and evaluate large deep learning models for robotic manipulation tasks.
• Develop frameworks to continuously improve robot behaviors.
• Collaborate with product teams to align on customer requirements for on-site deployments.
• Own scenario setup and data collection methodologies for unique customer use-cases.
• Ensure robots are deployment-ready and support full-stack deployments at customer sites.
• Build robust testing and evaluation pipelines for model improvements and corner cases.

Skills

Python

PyTorch

TensorFlow

JAX

Computer vision

Robotics

Reinforcement learning

Imitation learning

Model training

ROS/ROS2

Education

BS/MS/PhD in Computer Science or Robotics

Tools

ROS/ROS2

Job description

Skild AI is seeking a Research Engineer to advance post-training and deployment of foundation models on real robots. You will improve models and deploy them in field environments, collaborating with customers to ensure reliable, safe robotic behavior.

As part of the post-training team, you will own data collection, build evaluation pipelines, and coordinate with robotics teams to enable on-site deployments across diverse tasks, scaling robust performance in real-world settings.