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Lead AI & Machine Learning Infrastructure Engineer
Remote / San Francisco, CA
$180,000 – $230,000 + Equity
Immediate Interview Queue
About the Role
An enterprise AI platform is seeking a Lead AI/ML Infrastructure Engineer to architect, optimize, and maintain high-performance GPU clusters, model training pipelines, and low-latency inference endpoints at scale.
You will be responsible for orchestrating Kubernetes clusters for distributed training (PyTorch, DeepSpeed, vLLM), establishing automated CI/CD for model weights, and reducing inference latency.
Qualifications & Skills
• 6+ years in software engineering with 3+ years dedicated to ML Ops or AI infrastructure.
• Deep experience with PyTorch, CUDA, Triton Inference Server, and Hugging Face pipelines.
• Proven track record running large-scale Kubernetes clusters (EKS/GKE) with GPU nodes.
• Experience with vector databases (Pinecone, Qdrant, Milvus, pgvector) and RAG pipelines.
• Passion for cutting-edge LLM serving and distributed computing frameworks.
Benefits & Perks
- Top-tier equity grant in a high-growth AI unicorn
- Comprehensive medical, dental, and life insurance
- Flexible remote work environment with option for hybrid in SF office
- Latest M3 Max MacBook Pro + dual 4K display setup provided
- Commuter & wellness benefits
The Pivett Candidate Journey
1. Recruiter Screen20-min alignment call on stack & compensation
2. Tech EvaluationPractical coding review with senior staff
3. Client IntroFast-track interview with engineering lead
Quick Application
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Direct submission to the dedicated hiring recruiter.