The Role
We are seeking a researcher to drive forward our work in game theory, developing proofs of concept, reviewing literature, and implementing cutting-edge research. Ideal candidates include PhD students in game theory or authors of relevant papers. While deep engineering expertise is not required, candidates must demonstrate proficiency in C++ and Python.
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.
Apply reinforcement learning and search-based techniques to enhance game-solving strategies and opponent modeling.
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