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0.0 years
2 Lacs
bengaluru, karnataka, india
On-site
Reinforcement Learning: Strong understanding of the fundamentals of reinforcement learning, including concepts like Markov Decision Processes, Q-learning, and policy gradients. Experience with modern RL libraries like OpenAI Gym, Ray's RLlib, or Stable Baselines. Practical knowledge of reinforcement learning in non-stationary environments and using human feedback as rewards. Computational Skills: Proficiency in Python and other programming languages common in the AI/ML domain. Knowledge of GPU and TPU computation, especially in the context of deep learning. Deep Understanding of LLMs: Familiarity with the nuances of large language models, their strengths, and potential pitfalls. Awareness of...
Posted 1 week ago
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