Engineering Manager, MLOps- San Antonio, Austin, or Dallas, TX

Responsibilities We are seeking an experienced and dynamic individual to lead our MLOps team as a MLOps Team Manager. The ideal candidate will have 3-5 years of hands‑on experience managing MLOps teams, possessing a strong background in Data Science or AI teams with exposure to MLOps practices. This position offers a unique opportunity to contribute to our innovative approach in Site Reliability Engineering for Machine Learning while collaborating closely with Data Scientists and their leadership. Our Partners thrive The H-E-B Way. As a Senior Manager of Data Solutions, Machine Learning Operations, you have a... HEART FOR PEOPLE... you have a passion for mentorship and guidance, and love for the direct person‑to‑person interactions that create strong bonds between teams HEAD FOR BUSINESS... you have an ownership mentality and a consistent track record of timely delivery of high‑quality software PASSION FOR RESULTS... the ability to guide the discussion, remove roadblocks, and provide guardrails for your team as they identify challenges and propose solutions What You’ll Do Lead and manage the MLOps team, fostering a collaborative and high-performance culture. Collaborate with Data Scientists and their leadership as key stakeholders/customers, providing support and aligning technical strategies with business goals. Drive the implementation and optimization of MLOps practices to ensure seamless integration of machine learning models into production environments. Oversee the end‑to‑end ML lifecycle, including data preprocessing, feature engineering, model training, validation, and deployment. Utilize your expertise in ML concepts (supervised, unsupervised, semi‑supervised, and reinforcement learning) to guide the team's decisions and strategies. Ensure the team's cloud expertise by leveraging 3‑5 years of experience with AWS (preferred), Azure, and/or Google Cloud Platform (GCP). Manage direct reports within the team, fostering their professional growth and development. Collaborate with cross‑functional teams to establish best practices, standards, and continuous improvement processes. Who You Are Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (advanced degree preferred). 5‑7 years of experience managing MLOps teams, or comparable experience leading Data Science or AI teams with a focus on MLOps. Strong understanding of Site Reliability Engineering (SRE) principles and their application in machine learning contexts. Proficiency in cloud platforms, with hands‑on experience in AWS, Azure, and/or GCP. Deep understanding of machine learning concepts including supervised, unsupervised, semi‑supervised, and reinforcement learning. Proven track record of successfully deploying machine learning models into production environments. Strong grasp of the end‑to‑end ML process including data preprocessing, feature engineering, model training, validation, and deployment. Excellent communication skills with the ability to collaborate effectively across technical and non‑technical teams. Experience managing direct reports and fostering their growth. Strong problem‑solving skills and ability to adapt to a fast‑paced, evolving environment. #J-18808-Ljbffr H-E-B