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Senior Software Engineer, Machine Learning Infrastructure & Automation

fal.ai· Engineering
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Remote$170k - $230kFull-timePosted 2w ago

About the role

Role focused on building automation, infrastructure, and developer tooling to accelerate ML model development, testing, and deployment. Owns ML CI/CD systems, automated model validation, performance benchmarking, and AI-powered workflows to reduce toil and improve reliability.

Responsibilities

  • Own ML CI/CD infrastructure Design, build, and maintain automated testing, validation, and deployment pipelines for our ML models and inference services.
  • Accelerate development cycles.Dramatically reduce CI execution times through intelligent parallelization, caching, test selection, and efficient use of compute resources.
  • Build automated model validation.Develop systems that test model outputs, detect quality regressions, and validate changes across different models, GPU architectures, and configurations.
  • Automate performance benchmarking. Build continuous performance testing that detects regressions in inference latency, throughput, GPU utilization, and cost.
  • Build automated pricing and deployment checks. Ensure model pricing, billing configurations, API schemas, and deployments are validated automatically before reaching production.
  • Extend our agentic engineering workflows. Develop AI-powered automation and agentic coding systems that automatically diagnose CI failures, identify regressions, propose fixes, and streamline engineering workflows.
  • Improve deployment reliability. Build automated safeguards, deployment verification, rollback mechanisms, and monitoring to ensure new model releases are reliable.
  • Eliminate engineering toil. Identify repetitive tasks across the ML team and build tools and systems that automate them, allowing engineers to focus on developing new models and improving performance.

Qualifications

  • 5+ years of software engineering background with proficiency in Python and experience building production infrastructure and developer tooling.
  • Experience designing and operating CI/CD systems using GitHub Actions or comparable technologies.
  • Deep understanding of automated testing, build systems, dependency management, caching, and parallel execution.
  • Experience working with containerized workloads, Docker, and cloud infrastructure.
  • Ability to design reliable distributed systems and debug complex infrastructure failures.
  • Strong understanding of observability, including logs, metrics, tracing, and automated alerting.
  • A passion for developer productivity and a demonstrated ability to eliminate manual processes through automation.
  • Comfortable working independently, identifying high-impact problems, and building end-to-end solutions.
  • Experience with ML infrastructure, PyTorch, GPU workloads, or model-serving systems.
  • Familiarity with NVIDIA GPU architectures and multi-GPU environments.
  • Experience building automated inference benchmarks or ML quality evaluation frameworks.
  • Experience with agentic coding tools such as Codex or Claude Code, or building custom AI engineering agents.
  • Experience optimizing CI/CD pipelines at scale, including distributed test execution and ephemeral compute environments.
  • Experience developing internal developer platforms or infrastructure-as-code tooling.

Skills

Required:PythonCI/CDGitHub ActionsAutomated testingDockerCloud infrastructureObservability
Nice to have:ML infrastructure

Benefits

  • Health, dental, and vision insurance (US)
  • Regular team events and offsites
  • Interesting and challenging work
  • A lot of learning and growth opportunities
Last updated Oct 10, 2026. Interested? Apply on the company site.

About fal.ai

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