ML Infra Engineer - Real-Time Weather AI (Hybrid)

WindBorne Systems; Atlanta (GA); Hybrid; USD 140,000 - 240,000; Full time

Benefits offered by this job

401(k)

Dental, health, and vision insurance

Unlimited PTO

Stock Option Plan

Office food and beverages

Job summary

WindBorne Systems is building AI weather models and real-time forecasts from a global balloon network. We seek a systems-minded ML engineer to reduce firefighting by improving data pipelines, training infra, and deployment reliability.

You’ll own end-to-end uptime, scale inference, and manage data from dozens of sources, with a fast-paced research team and on-prem plus cloud deployments.

Qualifications

• Experience running production ML systems.
• Experience with large datasets.
• Experience with fast-paced model releases and reliable deployments.
• Experience with PyTorch, Docker, memory management, compression, and debugging network saturation.
• Affinity for systems and structured infra.

Responsibilities

• Research to Operations pipelines — own uptime end-to-end: build health monitoring, logging, diagnose failures across nodes.
• Inference scaling & compute strategy — evaluate cost/performance across cloud options and manage on‑prem resources as we scale.
• Data pipelines & upstream reliability — build pipelines for training and realtime data with QC checks and logging/alerts for edge cases.
• Training infrastructure — make distributed training runs reliable with monitoring, auto-recovery, and job scheduling so researchers can launch experiments with less babysitting.

Skills

Production ML

Large datasets

Model release

PyTorch

Docker

Memory management

Network debugging

System reliability

Tools

Docker

Job description

WindBorne Systems is building AI weather models and real-time forecasts from a global balloon network. We seek a systems-minded ML engineer to reduce firefighting by improving data pipelines, training infra, and deployment reliability.

You’ll own end-to-end uptime, scale inference, and manage data from dozens of sources, with a fast-paced research team and on-prem plus cloud deployments.