Opportunity Description
Job Description
Must Have Technical/Functional Skills
Experience:
3+ years building and deploying enterprise scale decision systems. Hands-on experience with implementing policy gradient methods (PPO, A3C), value-based approaches (DQN, Q-learning) and off-policy algorithms. Deep familiarity with the Bellman equation, reward shaping, exploration-exploitation tradeoff, constraint mapping and knowing common failure points of real-world reinforcement learning systems. Ability to diagnose issues with policy learning and collapse, credit assignment issues, and distributional shifts affecting performance of the model.
Key Skills:
Deep learning frameworks (tensorflow, pytorch), linear programming, Markov decision processes, Actor-Critic methods, Offline RL methods (CQL, Decision Transformer), probabilistic modeling, databricks, Ray RLLib, Gymnasium, PettingZoo (MARL).
Must Have Technical/Functional Skills
Experience:
3+ years building and deploying enterprise scale decision systems. Hands-on experience with implementing policy gradient methods (PPO, A3C), value-based approaches (DQN, Q-learning) and off-policy algorithms. Deep familiarity with the Bellman equation, reward shaping, exploration-exploitation tradeoff, constraint mapping and knowing common failure points of real-world reinforcement learning systems. Ability to diagnose issues with policy learning and collapse, credit assignment issues, and distributional shifts affecting performance of the model.
Key Skills:
Deep learning frameworks (tensorflow, pytorch), linear programming, Markov decision processes, Actor-Critic methods, Offline RL methods (CQL, Decision Transformer), probabilistic modeling, databricks, Ray RLLib, Gymnasium, PettingZoo (MARL).
Ready to Apply?
Submit your application for Decision Intelligence Engineer at ClifyX, INC
Apply for this Position