About the Internship
As a Reinforcement Learning Intern, you will play a critical role in the lifecycle of machine learning projects by ensuring high-quality, well-structured data that meets model requirements.Selected intern’s day-to-day responsibilities include:
1. Design, implement, and train reinforcement learning models for robotic locomotion.
2. Independently develop a functional proof of concept (PoC) for control tasks.
3. Integrate RL policies into physics-based simulation environments (e.g., PyBullet, MuJoCo, Isaac Gym).
4. Develop solutions for obstacle avoidance and terrain adaptation.
5. Test and analyze performance of RL models across various terrains and loading conditions.
6. Conduct research and experimentation to improve model robustness and generalization.
7. Collaborate with team members after initial PoC for real-world feasibility studies.
8. Debug model convergence issues and fine-tune hyperparameters for optimal results.
Number of Openings
1 openingsPerks of this Internship
Certificate Recommendation letter Informal dress code
Other Requirements
1. are available for full time (in-office) internship
2. have relevant skills and interests
3. can start the internship between 23rd Jul'25 and 27th Aug'25
4. are available for duration of 6 months
5. have already graduated or are currently in any year of study
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