Senior Software Engineer Machine Learning Infrastructure and Automation

You will build and maintain automated testing, validation, and deployment pipelines for machine learning models and inference services. You will improve CI execution through parallelization, caching, test selection, and efficient compute use. You will create model-quality and performance benchmarks, validate pricing and deployment configurations, develop AI-powered CI diagnostics, and add deployment safeguards, rollbacks, and monitoring. You will identify repetitive engineering work and automate it.

Responsibilities

• Build and maintain automated testing, validation, and deployment pipelines for ML models and inference services
• Reduce CI execution times through parallelization, caching, test selection, and efficient compute use
• Develop automated model validation across models, GPU architectures, and configurations
• Build continuous inference performance benchmarks
• Validate model pricing, billing configurations, API schemas, and deployments before production
• Develop AI-powered systems that diagnose CI failures, identify regressions, and propose fixes
• Build deployment safeguards, verification, rollback mechanisms, and monitoring
• Automate repetitive ML engineering tasks

Requirements

• 5+ years of software engineering experience
• Python proficiency
• Production infrastructure and developer tooling experience
• CI/CD systems experience
• Automated testing, build systems, dependency management, caching, and parallel execution knowledge
• Containerized workload, Docker, and cloud infrastructure experience
• Distributed systems design and infrastructure debugging ability
• Observability knowledge, including logs, metrics, tracing, and alerting

Benefits

• Equity
• Health, dental, and vision insurance
• Regular team events and offsites