AI Infrastructure Engineer — ML Production, Equity & Flexible Work

Gray Swan Ai; Pittsburgh (Allegheny County); On-site; USD 130,000 - 185,000; Full time

Benefits offered by this job

401k with up to 4% matching

28 days annual leave

Health, dental, and vision coverage

Catered lunches (Pittsburgh office)

Flexible work arrangements

Visa sponsorship available for extreme

Job summary

Gray Swan Ai is hiring a Software Engineer, AI Infrastructure to bridge ML research and production systems in Pittsburgh. You will build the infrastructure, tooling, and workflows that move models from experimentation into reliable production environments, while improving developer experience and scalability.

Join a fast-moving team that values ownership, practical solutions, and collaboration with ML engineers and researchers to deliver real-world impact in AI safety and security.

Qualifications

• Proven experience building production-grade ML infra and tools.
• Strong Python and backend development skills.
• Experience with cloud platforms and distributed systems.
• Ability to translate customer needs into scalable software.
• Comfort working with ML researchers to accelerate deployment.

Responsibilities

• Build and maintain infrastructure enabling ML models from experiments to production.
• Develop internal tools to improve model training, evaluation, and iteration.
• Design systems for evaluation pipelines, orchestration, reproducibility, and monitoring.
• Collaborate with ML engineers to address bottlenecks and scale deployments.
• Translate customer requirements and policy needs into engineering solutions.
• Improve reliability, scalability, and observability of ML capabilities.

Skills

Python

Backend systems

APIs

Cloud infrastructure

Distributed systems

Containerization

Kubernetes

Docker

ML workflows

Model training

Tools

Kubernetes

Docker

AWS

GCP

Ray

Kubeflow

MLflow

Weights & Biases

Job description

Gray Swan Ai is hiring a Software Engineer, AI Infrastructure to bridge ML research and production systems in Pittsburgh. You will build the infrastructure, tooling, and workflows that move models from experimentation into reliable production environments, while improving developer experience and scalability.

Join a fast-moving team that values ownership, practical solutions, and collaboration with ML engineers and researchers to deliver real-world impact in AI safety and security.