Decision Intelligence Engineer
Listed on 2026-06-27
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Engineering
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 (tensor flow, pytorch), linear programming, Markov decision processes, Actor-Critic methods, Offline RL methods (CQL, Decision Transformer), probabilistic modeling, databricks, Ray RLLib, Gymnasium, Petting Zoo (MARL).
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