🛠 Tech Stack

💼 About This Role

You'll lead GPU benchmarking for machine learning workloads at Nebius, a full-stack AI cloud platform. Your work will directly influence platform optimisation and next-gen hardware development. You'll collaborate with experts across hardware and software teams.

🎯 What You'll Do

• Profile and analyze GPU performance at system and kernel level
• Compare GPU performance across platforms and software stacks
• Debug and optimize ML workloads for GPU efficiency
• Perform acceptance testing for new GPU clusters

📋 Requirements

• Deep understanding of theoretical ML foundations
• Experience with deep learning frameworks (PyTorch, JAX, Megatron-LM)
• Knowledge of GPU stack (CUDA, NCCL, drivers)
• Familiarity with containerized environments (Docker, Kubernetes)

✨ Nice to Have

• Familiarity with LLM inference frameworks (vLLM, SGLang)
• Proficiency in Python and performance profiling tools
• Contributions to open-source ML benchmarking

🎁 Benefits & Perks

• 💰 Competitive compensation
• 📈 Career growth and learning
• 🏖️ Flexibility and work-life balance
• 🤝 Collaborative culture
• 🌍 International environment

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3System design· 60 min
4. 4Offer· 30 min