Lead Machine Learning Engineer - Merchandising AI (ML Ops)

• 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
• MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience in applied machine learning
• 5 plus years of experience in end-to-end machine learning application development, including data pipelining, model optimization, deployment and API design
• Extensive experience with applied machine learning frameworks and the ability to developing highly distributed machine learning systems at scale
• Highly proficient in Python programming
• Strong understanding of CI/CD practices for machine learning systems and ML Ops principles
• Extensive experience with Google Cloud's Vertex AI and/or the broader cloud-based ML ecosystem
• Demonstrated knowledge of various testing frameworks and containerization like Docker and Kubernetes
• Lead the development of agentic AI solutions that connect data, tools, APIs and business rules into end-to-end decisioning workflows
• Demonstrated experience in REST API design and development
• Extensive understanding of Big Data technologies including Hadoop, Spark and Kafka
• Proven ability to collaborate with data scientists, software engineers and product managers to deliver scalable machine learning solutions
• Excellent communication skills with an ability to tell data-driven stories through visualizations and narratives
• Ability to mentor engineers and help establish engineering standards, architecture patterns, and best practices for AI/ML and cloud-native development.
• Self-driven, results-oriented and able to meet tight deadlines
• Motivated team player who thrives in a collaborative global environment

This position may be considered for a Remote or Hybrid (known internally at Target as "Flex for Your Day") work arrangement based on Target's needs.  A Remote work arrangement means the team member works full-time from home or an alternate location that's not a Target location, does not have a desk at a Target location and may travel to HQ up to 4 times a year.  A Hybrid/Flex for Your Day work arrangement means the team member's core role may be performed either remote or onsite at a Target location depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target.