
Game Solving Researcher(Cuda, C++)
1 day ago
**The Role**
**Your responsibilities**:
- Design and develop advanced game-solving algorithms with a focus on optimizing Counterfactual Regret Minimization (CFR) for large-scale imperfect information games.- Implement and fine-tune CFR variants, including Monte Carlo CFR (MCCFR), vectorized CFR, to improve computational efficiency, quality of the solutions and convergence speed.-
- Analyze and improve the performance of game-solving AI by implementing regret minimization strategies, function approximation methods, and neural network-assisted CFR techniques.- Collaborate with AI researchers and game engineers to integrate game-solving AI into production systems and evaluate real-world performance.
**What you bring to the table**:
- 3+ years of experience in game theory, reinforcement learning, or AI for strategic decision-making.- Expertise in CFR algorithms and their optimizations, including variants like MCCFR, vectorized CFR, depth-limited CFR, and regret matching techniques.- Deep understanding of reinforcement learning, including value-based and policy-based methods.- Familiarity with search-based planning methods such as Monte Carlo Tree Search (MCTS).- Strong mathematical foundation in probability, statistics, optimization, and game theory.
**Preferred qualifications**:
- PhD or Master’s in Computer Science, Machine Learning, AI, Mathematics, or a related field.- Proven track record of research publications in game theory, reinforcement learning, or multi-agent systems.- Strong analytical skills and a collaborative mindset.- Ability to write in Python and C++
**Nice to have**:
- Experience with Poker, solvers, and solution libraries- Experience with CUDA- 2+ years of commercial experience- 3+ years of C++ experience
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