🛠 Tech Stack

💼 About This Role

You'll design and develop advanced reinforcement learning algorithms for real-world applications, working with a globally distributed research team. Your core impact will be optimizing decision-making across dynamic environments through large-scale RL experimentation and deployment.

🎯 What You'll Do

• Design and implement advanced RL algorithms for decision-making optimization.
• Build and execute large-scale RL experiments, tracking KPIs and benchmarks.
• Optimize RL pipelines for exploration stability and computational efficiency.
• Integrate RL agents into production systems for real-world applications.
• Contribute to AI research exploring innovative RL methodologies.

📋 Requirements

• Degree in CS, AI, or ML; PhD preferred.
• Strong research background in reinforcement learning.
• Hands-on experience with large-scale RL experiments and online methods like GRPO.
• Deep understanding of policy gradients, actor-critic, and optimization techniques.
• Expertise in PyTorch and RL frameworks for end-to-end pipelines.

✨ Nice to Have

• Experience deploying RL systems in production or large-scale research.
• Work with multi-modal AI and resource-efficient architectures.

🎁 Benefits & Perks

• 🏖️ Fully remote work with global collaboration.
• 🔬 Cutting-edge AI research opportunities.
• 🌍 International team of AI researchers and engineers.
• 📈 Career growth in a rapidly evolving tech environment.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter call· 30 min
2. 2Technical interview· 60 min
3. 3Research presentation· 45 min
4. 4Team fit interview· 30 min