🛠 Tech Stack

💼 About This Role

You'll own image management, deployment, and validation across GPU-enabled infrastructure for AI workloads. You'll lead system validation and diagnostics to ensure production-ready environments from day one. Collaborate with cross-functional teams to scale compute for the future of AI.

🎯 What You'll Do

• Evolve image management and deployment systems for GPU environments
• Lead GPU diagnostics and validation workflows
• Build automation tools in Python for provisioning
• Support hardware qualification for new platforms

📋 Requirements

• 5+ years of infrastructure engineering experience
• Strong Linux systems administration in production
• Hands-on experience with GPU-enabled systems and NVIDIA DCGM
• Proficiency in Python for automation

✨ Nice to Have

• Experience with high-performance interconnects (InfiniBand, NVLink)
• AI/ML or HPC workload experience
• Large-scale hardware validation frameworks

🎁 Benefits & Perks

• 💰 Competitive salary $180k-$200k
• 📈 Performance bonus and equity
• 🩺 Medical, dental, vision coverage
• 🏖️ Generous PTO and paid parental leave
• 🏡 Flexible remote work options

📨 Hiring Process

Estimated timeline: 2-3 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3Hiring manager round· 45 min