Job opportunity RL research engineer

A friend is searching for talented reinforcement learning research engineer

🚀 Calling all Reinforcement Learning Wizards! ✨ 🚀

We’re on the hunt for a brilliant Applied Machine Learning Engineer – Reinforcement Learning to join our team in Paris! 🇫🇷

Are you obsessed with pushing the boundaries of RL? Do you dream in AlphaZero and MuZero? If so, you might be the perfect fit! We’re working on groundbreaking applications of RL in real-time strategy simulations and need your expertise to take things to the next level.

What you’ll be doing:
🧠 Design, implement, and optimize cutting-edge RL algorithms.
🤝 Collaborate with talented teams to bring those algorithms to life.
🔥 Explore innovative ways to supercharge performance in complex, multi-agent environments.
🛠️ Work with state-of-the-art tools & frameworks (PyTorch, JAX, and more!)
🔬 Contribute to building our own tools to accelerate RL research.
📚 Stay on top of the latest RL advancements and apply them to real-world challenges.

What you’ll need:
💪 Deep expertise in Reinforcement Learning, especially model-based approaches.
🧑‍💻 Proven experience implementing advanced algorithms like AlphaZero, MuZero, etc.
⚙️ Proficiency in machine learning frameworks (PyTorch or JAX).
📈 A strong background in designing and training neural networks for dynamic environments.
🎮 A passion for real-time strategy (RTS) games or simulations (huge plus!).
🐍 Solid Python coding skills (C++ experience a bonus!).
🌐 Familiarity with distributed training, multi-agent systems, and optimization.
🧐 Strong analytical and problem-solving skills, always thinking about performance and scalability.

Bonus Points:
📜 Master’s or Ph.D. in Computer Science, Machine Learning, or related field (or equivalent experience).
✍️ Prior experience publishing RL research.
If this sounds like your dream job, we’d love to hear from you! Come join us and let’s build the future of AI together! 🚀

Contact me on linkedinhttps://www.linkedin.com/in/rabihamhaz?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=ios_app