AI Platform Engineer: Production ML & Kubernetes

Lightning AI; New York (NY); Hybrid; USD 115,000 - 140,000; Full time

Benefits offered by this job

Health coverage

Equity (RSUs)

401(k) matching

Unlimited PTO

Hybrid work model

Office meals

Job summary

Lightning AI is hiring an AI Platform Support Engineer to join our US Customer Experience team, supporting ML engineers running large-scale training and inference workloads across cloud infrastructure, Kubernetes, and GPU platforms in production.

You will be a technical partner to ML teams, diagnosing failures, improving reliability, and guiding customers through complex distributed systems problems in a hybrid role out of Seattle, SF, or NY with 2 days in-office per week.

Qualifications

• Strong software engineering and systems troubleshooting background.
• Experience with Kubernetes and containerized environments.
• Linux knowledge including networking, storage, and performance tuning.
• Cloud infrastructure and distributed systems experience.
• Observability and debugging tools such as Prometheus, Grafana, or OpenTelemetry.
• Hands-on experience operating machine learning workloads in production or research environments.
• Experience with PyTorch, CUDA, or NCCL; familiarity with GPU infrastructure.

Responsibilities

• Partner with customer engineering teams running training and inference workloads in production.
• Diagnose and resolve complex distributed systems and ML infrastructure issues.
• Act as a technical advisor during high impact incidents and platform degradation events.
• Translate infrastructure issues into actionable guidance for ML engineers.
• Build credibility with customers through strong technical reasoning and clear communication.
• Investigate failures involving distributed training, Kubernetes, GPU allocation, networking, and storage.
• Troubleshoot PyTorch, CUDA, NCCL, and inference serving issues; analyze logs and traces.
• Debug containerized workloads across Kubernetes and bare metal GPU environments.
• Support customers scaling workloads across multi-node GPU systems.
• Identify recurring patterns and drive long-term reliability improvements.

Skills

Kubernetes

Linux

Python

Distributed systems

Cloud infrastructure

Observability

PyTorch/CUDA

Networking

Education

Bachelor's degree in CS or related field

Tools

Kubeflow

Ray

Slurm

Prometheus

Grafana

OpenTelemetry

Job description

Lightning AI is hiring an AI Platform Support Engineer to join our US Customer Experience team, supporting ML engineers running large-scale training and inference workloads across cloud infrastructure, Kubernetes, and GPU platforms in production.

You will be a technical partner to ML teams, diagnosing failures, improving reliability, and guiding customers through complex distributed systems problems in a hybrid role out of Seattle, SF, or NY with 2 days in-office per week.