Software Engineer - ML Infrastructure

Gray Swan AI • Pittsburgh, PA

1d • $130,000 - $185,000

About The Position

Gray Swan is seeking a software engineer to work at the intersection of machine learning, software engineering, and production infrastructure. The role partners closely with the ML team to build systems, tools, and workflows that move models from experimentation into reliable production environments. The engineer will improve developer experience for model training and evaluation, build scalable infrastructure for ML workflows, and translate customer requirements and policy considerations into practical technical solutions. The position is suited to a software engineer who enjoys complex infrastructure challenges and collaborating with ML researchers and engineers to accelerate development and deliver real-world impact.

Requirements

• Experience building and maintaining production-grade systems, services, or infrastructure.
• Experience with Python and comfort working across backend systems, APIs, and infrastructure code.
• Familiarity with cloud infrastructure, distributed systems, containerization, or platform engineering.
• Knowledge of ML workflows, including model training, inference, evaluation, or deployment.
• Ability to collaborate with ML engineers and researchers to translate complex technical requirements into reliable software.
• Ability to navigate ambiguity, identify problems independently, and deliver practical solutions in a fast-moving environment.

Nice To Haves

• Experience building ML infrastructure, ML platforms, or internal developer tooling.
• Familiarity with Kubernetes, Docker, and cloud platforms such as AWS or GCP.
• Experience with ML infrastructure tools such as Ray, Kubeflow, MLflow, or Weights & Biases.
• Experience with model serving, distributed training, inference infrastructure, or large-scale evaluation pipelines.
• Exposure to AI safety, AI security, adversarial testing, or model behavior evaluation.
• Experience translating customer requirements, security constraints, or policy considerations into technical implementations.

Responsibilities

• Build and maintain infrastructure, services, and deployment workflows that move ML models from experimentation into reliable production environments.
• Develop internal tools and automation to improve the developer experience for model training, experimentation, evaluation, and iteration.
• Design and optimize systems for model evaluation pipelines, experiment orchestration, reproducibility, and performance monitoring.
• Partner with ML engineers and researchers to identify infrastructure bottlenecks and build solutions that accelerate model development and deployment.
• Support customer-specific technical requirements and policy-driven workflows by translating evolving needs into practical, scalable engineering solutions.
• Improve the reliability, scalability, and observability of systems powering ML capabilities.

Benefits

• Competitive compensation package, with a salary range of $130,000–$185,000, plus performance-based bonus and meaningful equity package.
• 401k with up to 4% matching.
• 28 days annual leave, including vacation and holidays.
• Health, dental, and vision coverage.
• Catered lunches at the Pittsburgh office.
• Flexible work arrangements.
• Visa sponsorship available for exceptional candidates.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed