ML Engineer – Robotics

Jobtailor; Mountain View (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Jobtailor in Mountain View, CA, seeks an experienced ML robotics engineer to develop and optimize models for perception, motion planning, and control.

You will build computer vision and sensor-fusion pipelines, integrate with ROS/ROS2, and deploy in live environments, collaborating with hardware engineers to ensure robust performance. Experience with simulators and real-time deployment is essential.

Qualifications

• 3–10 years of experience in ML, robotics, or CV.
• Strong understanding of localization, SLAM, and control systems.
• Experience with simulation environments for training and testing.
• Hands-on deployment of ML models in real-time or embedded systems.

Responsibilities

• Develop and optimize ML models for perception, motion planning, and control.
• Build CV and sensor-fusion pipelines using camera, LiDAR, and IMU data.
• Integrate models with ROS/ROS2 in robotics software stacks.
• Design data collection, simulation, and RL data pipelines.
• Collaborate with robotics and hardware teams to deploy in live environments.
• Evaluate model performance and robustness across diverse scenarios.

Skills

Python

C++

PyTorch

TensorFlow

ROS/ROS2

Sensor fusion

ML model deployment

Tools

Gazebo

CARLA

MuJoCo

PyBullet

ROS tools

Job description

Responsibilities

• Develop and optimize ML models for perception, motion planning, and control.
• Build computer vision and sensor-fusion systems using camera, LiDAR, and IMU data.
• Integrate learning-based models with robotics software stacks (ROS/ROS2).
• Design pipelines for data collection, simulation, and reinforcement learning.
• Collaborate with robotics and hardware engineers to deploy models in live environments.
• Continuously evaluate model performance and robustness across diverse scenarios.

Requirements

• Proficiency in Python and C++, with hands‑on experience using PyTorch and/or TensorFlow to build and deploy models.
• Experience with ROS or ROS2 and integrating ML models into robotics software stacks for live deployments.
• 3–10 years of experience in machine learning, robotics, or computer vision.
• Strong grasp of robotics concepts such as localization, SLAM, control systems, and sensor fusion.
• Experience with simulation environments (e.g., Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet) for training, testing, or validation.
• Familiarity with reinforcement learning, imitation learning, or adaptive control techniques applicable to robotics.
• Experience deploying ML models in real‑time or embedded environments.
• Nice to Have: Experience with on‑board/edge deployment and optimizing models for constrained hardware.

Core Competencies

Demonstrates expertise in developing and optimizing machine learning models for robotics applications, with a strong focus on computer vision, sensor fusion, and real‑time deployment. Proficient in integrating learning‑based models with robotics software stacks and evaluating model performance in diverse environments.