🛠 Tech Stack

💼 About This Role

You'll build the foundation for Nuro's ML infrastructure, powering model development from experimentation to production. You'll design and optimize workload orchestration and data pipelines for large-scale autonomous driving. This role offers a chance to work on cutting-edge AI infrastructure at a leading self-driving company.

🎯 What You'll Do

• Scale automated Infrastructure-as-Code pipelines for GPU/CPU nodes.
• Design and optimize workload orchestration for distributed training.
• Build robust ETL pipelines for petabyte-scale sensor data.
• Implement feature caching and storage for low-latency access.
• Contribute to a unified ML platform abstracting cloud infrastructure.

📋 Requirements

• 5+ years of experience in ML Infrastructure or Distributed Systems.
• Deep familiarity with Terraform, Pulumi, or Crossplane.
• Hands-on experience with Kubernetes, Ray, or Slurm.
• Proficiency in Apache Spark or Apache Beam.

✨ Nice to Have

• Active contributor to open-source MLOps or Cloud-Native projects.
• Experience with high-performance storage systems like Lustre or Ceph.
• Knowledge of cost-optimization strategies for cloud GPU clusters.

🎁 Benefits & Perks

• 💰 Competitive base pay plus annual performance bonus and equity.
• 🏖️ Flexible time off and supportive work environment.
• ❤️ Comprehensive benefits including health, dental, and vision.
• 📈 Professional growth opportunities in cutting-edge autonomous driving.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Phone Interview· 60 min
3. 3Onsite Interviews (3-4 rounds)· half day