🛠 Tech Stack

💼 About This Role

You'll design and implement advanced RL algorithms for real-world applications, optimizing decision-making across dynamic environments. Your core impact will be building scalable, adaptive AI models that push the boundaries of performance. This role offers a remote-first environment within a globally distributed research team working on cutting-edge technologies.

🎯 What You'll Do

• Design and implement advanced reinforcement learning algorithms.
• Build, execute, and evaluate large-scale RL experiments.
• Develop and curate simulation environments and training datasets.
• Optimize RL pipelines for exploration, stability, and efficiency.

📋 Requirements

• Degree in Computer Science, AI, or related field; PhD preferred.
• Strong research background in reinforcement learning or AI.
• Hands-on experience with large-scale RL experiments and GRPO.
• Deep understanding of policy gradients, actor-critic methods, and PyTorch.

✨ Nice to Have

• Experience with multi-modal AI systems.
• Experience with resource-efficient model architectures.
• Proven ability to solve sample inefficiency and training instability.

🎁 Benefits & Perks

• 🏠 Fully remote work environment.
• 🤖 Cutting-edge AI and RL technologies.
• 🌍 Global collaboration with international researchers.
• 📈 Career growth in a rapidly evolving tech environment.
• 💡 Innovation-focused culture encouraging experimentation.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3Research presentation· 45 min