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Open nowPosted 354 days ago

ML Engineer - Robotics

Deccan AI13 open roles

Pay
$160,000 – $320,000 a yearly
Where
Mountain View, CA
Work mode
On site
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Your applicationOpen nowML Engineer - RoboticsDeccan AI · Mountain View, CA

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 354 days ago

The posting

About Us

Deccan AI is AI training, evaluations and Enterprise AI solutions startup headquartered in the Bay Area. We are founded by IIT Bombay, IIM Ahmedabad and ex-Google alumni, and work with some of the top AI frontier labs in the world. Backed by Prosus Ventures and A91 we are expanding the team in US, San Mateo.

About the Role

We’re looking for an ML Engineer – Robotics to design, train, and deploy intelligent models that power autonomous systems. You’ll work at the intersection of machine learning, control systems, and real-world robotics, helping to build perception, planning, and decision-making pipelines that make machines truly adaptive.

This role is ideal for someone who loves solving hard, interdisciplinary problems — combining data-driven learning with real-world constraints.

What You’ll Do

  • 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.

What You’ll Bring

  • 3–8 years of experience in Machine Learning, Robotics, or Computer Vision.
  • Proficiency in Python, C++, and frameworks such as PyTorch / TensorFlow.
  • Strong understanding of robotics concepts — localization, SLAM, control systems, or sensor fusion.
  • Experience with simulation environments (Gazebo, Isaac Sim, CARLA, Mujoco, or PyBullet).
  • Familiarity with reinforcement learning, imitation learning, or adaptive control techniques.
  • Solid grasp of deploying ML models in real-time or embedded environments.
  • Curiosity, grit, and passion for pushing the boundaries of embodied intelligence.
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