AI Research Engineer - (Immediate Joiners - Navi Mumbai)
- Jio
- 3 - 8 years
- Mumbai
- 4 months ago
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Job Description
Position Overview
We are looking for a passionate and skilled AI Research Engineer to join our team and advance the field of autonomous systems. In this role, you will focus on developing cutting-edge algorithms in Reinforcement Learning (RL), Imitation Learning, and Autonomous Decision-Making to enable robots to learn, adapt, and make decisions in complex, dynamic environments. You will work alongside other AI researchers and engineers to push the boundaries of autonomous decision-making in real-world robotics applications.
Key Responsibilities
- Conduct research and development in Reinforcement Learning (RL) and Imitation Learning to enable robots to learn complex tasks through both trial-and-error and expert demonstrations.
- Design and implement novel algorithms for autonomous decision-making, optimizing for efficiency, scalability, and robustness in dynamic environments.
- Develop methods for combining RL with other learning paradigms, such as supervised learning, unsupervised learning, and imitation learning, to improve the performance and generalization of autonomous systems.
- Work on reward engineering and exploration strategies for RL agents to enable fast and effective learning in real-world environments.
- Develop and implement simulation environments for training and evaluating RL and imitation learning algorithms, focusing on tasks such as navigation, manipulation, environment exploration and gait planning with dynamic environments.
- Design and evaluate approaches for transfer learning and domain adaptation to ensure that RL agents can transfer knowledge learned in one environment to new, unseen environments.
- Integrate RL and imitation learning algorithms into robotic platforms, ensuring they can function in real-time with the robot's sensors and actuators.
- Work closely with cross-functional teams, including robotics engineers, perception engineers, and software developers, to deploy decision-making algorithms in production environments.
- Perform thorough testing and validation of RL and imitation learning algorithms in both simulated i.e. Isaac Sim and real-world robotic systems i.e NVIDIAs Jetson hardware.
- Continuously monitor and improve the efficiency of learning algorithms, reducing training time and computational costs while maintaining high performance.
- Stay up-to-date with the latest research and advancements in reinforcement learning, imitation learning, and autonomous decision-making, applying relevant techniques to real-world applications.
- Contribute to the development of internal tools, frameworks, and libraries to support the deployment and scaling of RL algorithms in production systems.
Required Qualifications
- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Robotics, or a related field.
- Strong background in Reinforcement Learning (RL) and Imitation Learning, with hands-on experience applying these techniques to real-world problems (3+ years of research or industrial experience).
- Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or JAX, with experience in building and training RL agents using Isaac Lab.
- In-depth understanding of RL algorithms, including Q-learning, Policy Gradient methods, Actor-Critic, and deep RL techniques (e.g., DQN, A3C, PPO).
- Experience with Imitation Learning algorithms, such as Behavioral Cloning, DAGGER, or GAIL, and applying them in autonomous systems.
- Strong programming skills in Python, C++, or similar languages commonly used in AI and robotics.
- Experience with simulation platforms like Isaac Sim (Preferred) ,Gazebo, Unity, or PyBullet for RL agent training and evaluation.
- Familiarity with robotic systems, sensors, and actuators, and how to integrate AI algorithms with these hardware components.
- Ability to communicate complex AI research findings and algorithmic designs clearly to both technical and non-technical stakeholders.
- Strong analytical and problem-solving skills, with the ability to debug and optimize complex machine learning algorithms.
- Experience working with large-scale datasets and parallel or distributed computing frameworks is a plus.
Preferred Qualifications
- Experience with multi-agent reinforcement learning or cooperative decision-making in autonomous systems.
- Knowledge of safe exploration techniques and reward design in RL.
- Familiarity with cloud computing and distributed training infrastructure for AI and RL algorithms (e.g., AWS, Google Cloud).
- Experience in deploying RL-based decision-making systems in real-world applications such as robotics, autonomous vehicles, or drones.
- Contributions to open-source AI or reinforcement learning libraries, or published research in top AI conferences or journals.
Please Send CVs at
Kr*********n@te******t.in
Di***********h@te******t.in
Job Classification
Industry: Emerging Technologies (Drones/Robotics)Functional Area / Department: Other, Role Category: OtherRole: OtherEmployement Type: Full timeContact Details:
Company: JioLocation(s): Mumbai+ View Contact
Keyskills: Reinforcement Learning Machine Learning Deep Learning Artificial Intelligence
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₹ 16-27.5 Lacs P.A
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