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Explore jobs tagged reward-function to discover positions that require designing and evaluating reward functions for reinforcement learning, reward shaping, policy optimization, inverse RL, and reward modeling across robotics, game AI, recommendation systems, and ML safety teams. This list surfaces jobs (engineer, research scientist, applied ML, RL engineer) filtered by the reward-function tag within the jobs > tags pillar; use the filtering UI to narrow results by experience level, remote vs on-site, company, tech stack (PyTorch, TensorFlow), and domain. Get actionable insights on employer requirements—policy gradients, reward engineering, simulation environments, evaluation metrics, and production alignment—and optimize your resume and portfolio to match these long-tail skill needs. Browse current openings, save searches, and apply now to roles focused on robust reward design and alignment in production systems.