Senior MLOps Engineer

We are looking for a Senior MLOps Engineer. This role sits within the AI and data analytics team of a major automotive player, leading how the team operationalizes machine learning and raising MLOps maturity across the organization. Engagement details:Location: Auburn Hills, USAWorking model: HybridStart date: ASAPEmployment type: Full-time, Contract or Freelance Responsibilities:Lead the team's approach to MLOps and drive a modern, agile, and automated approach to data scienceDevelop, research, and implement MLOps frameworks, tools, and platforms for data science projectsDesign and implement infrastructure for machine learning cloud servicesBuild microservices for task-specific AI cloud servicesImplement model performance monitoring and alertingAutomate model retraining, monitoring, and versioning while improving code quality, security, and delivery speedCollaborate with the data platform team to create a feedback loop and improve the underlying data infrastructurePartner with peers to ensure scalability, business continuity, and appropriate turnaround timeOwn a backlog of activities to raise MLOps maturity and evolve the framework as new technologies emerge Qualifications:MSc / MEng in Statistics, Computer Science, Automatic Control, Engineering, or a related STEM discipline5+ years of professional coding experience in Python or other languages2+ years operationalizing data science projects (MLOps) with Databricks and MLflow5+ years with a cloud/DevOps stack (e.g., AWS, Docker, Kubernetes) and the ability to design complex architectureHands-on experience with PySpark and SQLProven track record converting data science prototypes into production and building scalable ML pipelines and servicesUnderstanding of distributed data systems and open source frameworksAbility to influence non-technical peers and leadership, and to mentor less experienced colleagues Nice to have: CI/CD/CT pipeline implementation, front-/backend development (Django, Node.js, Streamlit), shell scripting and networking, broad data science and statistics background Next steps:Press "Apply"We will review your applicationIf qualified, you will be accepted into the network and can be considered for this and similar positions & projects