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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.
Deccan AI is a model training and eval 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, e.g. Google Deepmind, Snowflake, and many more. We are backed by Prosus Ventures, and our India delivery office is in Hyderabad. Most of our roles are on-site i.e. Bay Area / Hyderabad. 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.
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.
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Continuously evaluate model performance and robustness across diverse scenarios.
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.
Provides high-quality training data and evaluation platforms for AI.
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Mid · 3+ years experience
Onsite
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