Reinforcement Learning (RL) Engineer (2 - 4 Years)

Job Description

We are seeking a highly skilled **Reinforcement Learning (RL) Engineer**to develop, implement, and optimize RL algorithms for real-world and simulation-based applications. The ideal candidate has strong foundations in machine learning, deep learning, control systems, and hands-on experience deploying RL models in production or embedded systems.

**Responsibilities**

* Design, implement, and optimize RL algorithms such as PPO, SAC, TD3, DQN,A3C, TRPO, etc.
* Develop custom reward functions, policy architectures, and learning workflows.
* Conduct research on state-of-the-art RL techniques and integrate into productor research pipelines.
* Build or work with simulation environments such as PyBullet, Mujoco, IsaacGym, CARLA, Gazebo, or custom environments.
* Integrate RL agents with environment APIs, physics engines, and sensor models.
* Deploy RL models on real systems (e.g., robots, embedded hardware, autonomous platforms).
* Optimize RL policies for latency, robustness, and real-world constraints.
* Work with control engineers to integrate RL with classical controllers (PID, MPC, etc.)
* Run large-scale experiments, hyper parameter tuning, and ablation studies.
* Analyse model performance, failure cases, and implement improvements.
* Work closely with robotics, perception, simulation, and software engineering teams.
* Document algorithms, experiments, and results for internal and external stakeholders.

**Skills Required :**

* Strong expertise in Python, with experience in MLframeworks like PyTorch or TensorFlow.
* Deep understanding of:

¦ Markov Decision Processes (MDP)

¦ Policy \& value-based RL

¦ Deep learning architectures (CNN, RNN,Transformers)

¦ Control theory fundamentals
* Experience with RL libraries (stable-baselines3, RLlib,CleanRL, etc.).
* Experience with simulation tools or robotics middleware(ROS/ROS2, Gazebo).

**Added Advantage :**

* Experience in robotics, mechatronic, or embedded systems.
* Experience with C for performance-critical applications.
* Knowledge of GPU acceleration, CUDA, or distributed training.
* Experience bringing RL models from simulation to real-world (Sim2Real).
* Experience with cloud platforms (AWS/GCP/Azure).

**Experience :**

* 2--4 years of hands-on RL experience (academic or industry).
* Published RL research papers (optional but preferred).

**Qualifications**

* Bachelor's/Master's/PhD in Computer Science, Robotics, AI, Machine Learning, or related field

**Location : **Technopark, Thiruvananthapuram****