Staff Machine Learning Systems & Reliability Engineer (Moveworks)

Description du poste

We are building AI-enabled product capabilities that improve through data, feedback, and real-world use We need the production systems that make those capabilities dependable: repeatable delivery, measurable quality, controlled learning loops, and reliable operation at scale We’re looking for a hands-on Staff Engineer who can move machine-learning models, agentic workflows, and self-learning approaches from promising prototypes into secure, observable, continuously deployable production systems This role sits at the intersection of ML systems, platform engineering, and site reliability engineering You will partner with ML, data, product, and infrastructure teams to create a paved path from experimentation to production—and take ownership of how those systems perform and evolve once deployed Design and build the production path for the complete ML lifecycle: data and feature preparation, training, experiment tracking, evaluation, artifact and model management, serving, monitoring, feedback collection, and retraining Build continuous-delivery workflows for models, prompts, agent workflows, data dependencies, and supporting services. Establish automated quality, safety, performance, and compatibility checks Implement safe rollout patterns such as shadow traffic, canaries, progressive delivery, feature flags, versioned artifacts, automated rollback, and operational kill switches Turn self-learning approaches into controlled production feedback loops. Build systems for collecting outcomes, validating feedback, maintaining lineage, triggering model refreshes, comparing candidates, and promoting changes under explicit guardrails Define and operate SLIs, SLOs, alerts, and error budgets across infrastructure, data pipelines, inference services, model quality, and product behavior Connect model analytics and product telemetry with traditional operational signals so teams can understand whether a problem originates in infrastructure, data, model behavior, or the surr

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