Staff ML Engineer

Being good neighbors – helping people, investing in our communities, and making the world a better place – is who we are at State Farm. It is at the core of how we operate and the reason for our success. Come join a #1 team and do some good! HYBRID: Qualified candidates must live or relocate within a 180-mile radius of a hub location listed below and should plan to spend time working from home and some time working in the office as part of our hybrid work environment. HUB LOCATIONS: Bloomington, IL; Dunwoody, GA; Richardson, TX; or Tempe, AZ  SPONSORSHIP:  Applicants for this position are required to be eligible to lawfully work in the U.S. immediately; employer will not sponsor applicants for U.S. work authorization (e.g. H-1B visa) for this opportunity Responsibilities We are seeking a hands-on Staff Machine Learning Engineer to architect, build, and scale enterprise-grade AI/ML systems, real-time decisioning capabilities, and agentic AI applications. This role will help develop our next-generation Next Best Action (NBA) and recommendation platform, leveraging Databricks, AWS, and modern AI/ML technologies. The focus is on ML systems engineering, architecture, and productionization rather than developing predictive models from scratch. ML Architecture & Engineering: Design and build scalable, production-grade ML systems, APIs, feature pipelines, and reusable engineering components. Decisioning & Recommendation Engines: Architect real-time or near-real-time decisioning systems integrating predictive models, business rules, eligibility, prioritization, and optimization. Closed-Loop Learning: Build feedback mechanisms that capture customer interactions and business outcomes to continuously improve recommendations. Databricks & AWS Engineering: Develop reliable data and ML pipelines using Python, PySpark, SQL, Databricks, and AWS. MLOps: Implement model deployment, serving, versioning, monitoring, CI/CD, and retraining workflows. Agentic AI: Architect and develop production-grade agentic AI applications, including LLM orchestration, tool integration, evaluation, and guardrails. Technical Leadership: Lead architecture decisions, establish engineering standards, mentor engineers, and collaborate across technical and business teams.

Required  10+ years of experience in ML engineering, software engineering, or related technical disciplines, with demonstrated technical leadership. Programming: Expert-level Python and strong SQL skills; experience with APIs, microservices, and production software development. Data Engineering: Expert-level PySpark and Apache Spark; experience building reliable data and feature pipelines. Cloud & ML Platforms: Deep hands-on Databricks expertise (Delta Lake, Unity Catalog, Workflows) and strong AWS experience (S3, IAM, compute, and application integration). ML Engineering & MLOps: Experience supporting the full production ML lifecycle, including model integration, deployment, serving, monitoring, versioning, and retraining. Familiarity with MLflow and CI/CD. Real-Time Decisioning: Experience building low-latency inference services, decisioning APIs, and scalable recommendation systems. Agentic AI: Hands-on experience developing LLM-powered or agentic AI applications, including orchestration, tool calling, and enterprise integrations. System Architecture: Proven ability to independently architect and deliver complex, reliable enterprise systems. Preferred  Hands-on experience developing or training ML models. Experience building Next Best Action, recommendation, personalization, or decision optimization platforms. Familiarity with contextual bandits, reinforcement learning, uplift modeling, or ranking algorithms. Experience with LangGraph, LangChain, or similar agentic AI frameworks. Experience in insurance, financial services, or other regulated industries. Our Benefits Because work-life balance is a priority at State Farm, compensation is based on our standard