AI Research Engineer - Deep Learning

Key Responsibilities : - Lead the development and evolution of our AI core, currently built in C++, towards the next generation of algorithms and architectures. - The main responsibility is to lead the evolution of our AI core to the next level. - Included the opportunity to get visibility as an industry expert through the publishing of papers, conferences, and so on, to make it more appealing. - Design, implement, and optimize advanced RL algorithms tailored for imperfect information games. - Research and integrate state-of-the-art techniques in RL, neural networks, and game theory to enhance AI performance and scalability. - Collaborate with cross-functional teams to identify challenges and innovate AI-driven solutions. - Evaluate and fine-tune AI models for decision-making, strategy optimization, and real- time applications in gaming. - Profile, optimize, and troubleshoot the AI core for high-performance execution across different computing architectures (e.g., CPU, GPU, or custom accelerators). - Document methodologies, experiments, and results to ensure transparency and Skills and Qualifications : - Bachelors, Masters, or Ph.D. in Computer Science, Mathematics, Physics, Artificial Intelligence, or a related field. - 3 years of experience in AI/ML, with a strong focus on Reinforcement Learning and Neural Networks. - Proficiency in programming languages commonly used in AI, such as C++, Python, Julia, or others relevant to your expertise. - In-depth understanding of game theory, especially concepts like Nash equilibrium and strategies in imperfect information games. - Expertise in RL frameworks and tools like OpenSpiel, RLlib, or similar libraries tailored for game AI. - Strong knowledge of RL algorithms, and experience with neural network architectures. - Familiarity with parallel computing, performance profiling, and optimization techniques. - Excellent problem-solving skills, with the ability to work independently and in a Skills : - Experience with multi-agent RL or hierarchical RL in gaming contexts. - Background in poker AI or similar imperfect information games. - Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Knowledge of distributed systems, parallel programs, or cloud-based AI deployments. - Published research or contributions to open-source AI projects in RL or game AI. Soft Skills : - Effective communication for collaborating with cross-functional teams and presenting complex ideas clearly. - Passion for innovation and driving the next generation of AI in gaming. (ref:hirist.tech)

Location: chennai, IN

Posted Date: 4/18/2025