Location: Dallas, TX
Company: H-E-B Grocery Stores
hiring across the stack: front-end web and mobile, full-stack, and backend engineering. We're using the best available technologies to deliver modern, engaging, reliable, and scalable experiences to meet the needs of our growing audience. Our digital solutions are growing in popularity and adoption--like Curbside and Home Delivery--so you'll get the opportunity to define the user experience for millions of customers and hundreds of thousands of Partners.
If you're someone who enjoys taking on new challenges, working in a rapidly changing environment, learning new skills, and applying it all to solve large and impactful business problems, we want you as part of our team. 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.
DATA3232H-E-B Digital is seeking new team members (Partners)! Since our inception, we've been investing heavily in our customers' digital experience, reinventing how they find inspiration from food, how they make food decisions, and how they ultimately get food into their homes. This is an exciting time to join H-E-B Digital, and we're hiring across the stack: front-end web and mobile, full-stack, and backend engineering. We're using the best available technologies to deliver modern, engaging, reliable, and scalable experiences to meet the needs of our growing audience. Our digital solutions are growing in popularity and adoption--like Curbside and Home Delivery--so you'll get the opportunity to define the user experience for millions of customers and hundreds of thousands of Partners.
If you're someone who enjoys taking on new challenges, working in a rapidly changing environment, learning new skills, and applying it all to solve large and impactful business problems, we want you as part of our team. 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. DATA3232
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Engineering jobs encompass roles that involve applying scientific and mathematical principles to design, develop, and maintain structures, machines, materials, systems, and processes. These positions are characterized by innovation, problem-solving responsibilities, and the need for technical expertise. Engineers can specialize in various fields such as civil, mechanical, electrical, chemical, and software, among others. They are essential in shaping the infrastructure of the modern world, formulating solutions to complex challenges, and driving technological advancement. Engineering roles often require a strong educational background combined with practical experience, and they stand out for their contribution to societal progress and potential for career growth.
