AI Platform Support Engineer (AI)

Location: Hybrid in Seattle, San Francisco, or New York, with at least 2 days per week in the office; Monday–Friday, 8:00 AM–5:00 PM PST. Occasional team and company offsites are required.

Annual base salary: $115,000–$140,000 USD, plus discretionary bonus, equity, and benefits.

Company

hirify.global builds an end-to-end platform for developing, training, and deploying AI systems, combining developer-focused software with large-scale AI compute.

What you will do

• Partner directly with customer ML engineering teams running production training and inference workloads.
• Diagnose distributed systems and ML infrastructure issues involving Kubernetes, GPU allocation, networking, storage, and inference serving.
• Troubleshoot PyTorch, CUDA, NCCL, containerized workloads, and multi-node GPU systems.
• Analyze logs, metrics, traces, and system behavior to identify root causes and performance bottlenecks.
• Drive reliability improvements through post-incident reviews, observability, documentation, runbooks, and automation.
• Collaborate with infrastructure, networking, and platform engineering teams to improve customer troubleshooting workflows.

Requirements

• Strong software engineering and systems troubleshooting experience.
• Experience with Kubernetes, containerized environments, Linux, cloud infrastructure, and distributed systems.
• Knowledge of Linux networking, storage, process management, performance tuning, and observability tools such as Prometheus, Grafana, or OpenTelemetry.
• Hands-on experience operating machine learning workloads and troubleshooting distributed ML systems using tools such as PyTorch, CUDA, or NCCL.
• Experience with GPU infrastructure, orchestration, and ML infrastructure reliability, performance, or scaling issues.
• Visa sponsorship is not available for this role.

Nice to have

• Experience with large-scale model training, distributed inference, Ray, Kubeflow, Slurm, or similar scheduling platforms.
• Experience with InfiniBand, RDMA, high-performance networking, bare-metal infrastructure, or ML storage systems.
• Background in AI infrastructure, cloud, MLOps, developer tooling, or platform engineering.
• Experience writing Python automation, tooling, or scripts.

Culture & Benefits

• Health, dental, and vision coverage for employees and eligible dependents.
• RSUs, U.S. 401(k) matching, unlimited PTO, company holidays, and a two-week winter break.
• Paid parental and family leave, wellness and work-from-home stipends, and an annual learning allowance.
• Four weeks of paid sabbatical leave after four years of service.
• Flexible schedules, hybrid work, and complimentary meals at office hubs.