Senior ML Engineer - Deployment and Databricks MLOps

Senior ML Engineer - Deployment and Databricks MLOps | Austin, Texas, United States Senior ML Engineer - Deployment & Databricks MLOps 3-Month Contract (Potential Extension) | Austin, TX (On-site, Local Candidates Only) About the Role Join a high-impact team as a Senior ML Engineer, bringing advanced manufacturing AI/ML solutions to production. You'll design and operationalize robust Databricks-based MLOps platforms, enabling scalable, automated, and governed machine learning deployments in a dynamic on-site environment. Collaborate with talented data scientists, engineers, and platform specialists to build repeatable, production-ready AI workflows that power modern manufacturing. Responsibilities - Build, optimize, and maintain ML pipelines in Databricks for model training, validation, scoring, and deployment. - Implement and manage CI/CD pipelines for ML and data workflows using Git-driven development and automated testing. - Partner with data scientists and engineers to transition experimental models into production-ready assets with strong governance and traceability. - Develop and manage data/feature pipelines to support model retraining, monitoring, and operational integration. - Establish model lifecycle controls using MLflow and Unity Catalog, ensuring reproducibility, versioning, and controlled releases. - Enhance reliability and reduce deployment risk through rigorous data validation, monitoring, and workflow automation. - Support seamless deployment patterns extendable from R&D to plant-floor-ready solutions. Required Skills and Experience - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience). - Advanced Python software engineering for production ML systems. - Proven experience deploying ML models in production environments. - Deep hands-on experience with Databricks (jobs, workflows, repos, MLflow). - Expertise in building CI/CD pipelines for ML/data products using Git-based workflows. - Strong knowledge of data pipelines, feature engineering, batch processing, and workflow orchestration. - Collaborative experience in cross-functional ML, engineering, and cloud/platform teams. - Must be currently located within 30 miles of Austin, TX and able to work on-site 4-5 days/week. Preferred Skills - Background in manufacturing, industrial IoT, or plant-floor analytics. - Experience with model governance, lineage, and reproducible promotion of ML assets. - Designing resilient ML pipelines to handle evolving data and retraining needs. - Familiarity with operational model monitoring and validation. Benefits - Opportunity to shape the MLOps foundation for production-scale AI in manufacturing. - Work closely with leading experts in a collaborative, on-site Austin environment. - Gain hands-on experience with cutting-edge Databricks and MLflow technologies. - Build a reusable template for enterprise ML deployment and career advancement. - Contract with potential for extension based on performance and project needs. How to Apply Ready to lead enterprise AI deployment in manufacturing? If you are currently within 30 miles of Austin, TX and authorized to work without sponsorship, submit your resume today to join our innovative team!