Staff Machine Learning Systems & Reliability Engineer (Moveworks)

Join Moveworks, a company focused on building AI-enabled product capabilities. As a Staff Machine Learning Systems & Reliability Engineer, you will be responsible for creating dependable production systems for machine learning models and workflows. You will work closely with various teams to establish a seamless path from experimentation to production and take ownership of system performance and evolution. Your role will involve designing and building the complete ML lifecycle, implementing safe rollout patterns, defining and operating SLIs and SLOs, improving scalability and efficiency, and providing technical leadership across teams.

• Design and build the production path for the complete ML lifecycle, including data preparation, training, evaluation, artifact management, serving, monitoring, and retraining.
• Implement safe rollout patterns and turn self-learning approaches into controlled production feedback loops, building systems for collecting outcomes and validating feedback.
• Define and operate SLIs, SLOs, alerts, and error budgets across infrastructure, data pipelines, inference services, model quality, and product behavior.

• Experience distinguishing service-health problems from data-quality or model-quality problems
• Practical understanding of the ML lifecycle—including training, evaluation, model deployment, serving, monitoring, versioning, and retraining—and the ability to collaborate effectively with applied ML engineers or researchers
• Strong software-engineering skills in Python and at least one production systems language such as Go, Java, C++, or Rust
• Familiarity with SRE practices such as SLIs/SLOs, error budgets, sustainable on-call, incident management, and blameless postmortems
• Excellent technical judgment and communication skills, especially when navigating ambiguity and coordinating across teams during production incidents
• A track record of Staff-level technical ownership, typically gained through 7+ years of experience in software engineering, platform engineering, SRE, production engineering, or ML infrastructure
• Experience designing, operating, and troubleshooting distributed production systems, including failure analysis, capacity planning, and performance optimization
• A strong automation and internal-customer mindset: you build platforms that are reliable, understandable, and pleasant for other engineers to use
• Hands-on experience with cloud infrastructure, containers and Kubernetes, infrastructure as code, CI/CD, and modern observability