Lead Machine Learning Engineer - Merchandising AI (ML Ops) (Remote Eligible)

Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits., * 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., Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_E

Target offers comprehensive medical, dental and vision insurance plans. Plus, get free 24/7 virtual care and mental health support.

Financial well-being

Your financial future is bright with TGT 401(k) offering 5% eligible contribution matching and more discount and reimbursement programs.

Paid time off

Target encourages work-life balance by offering seven paid holidays, paid sick time, paid family leave, and a flexible paid time off plan that doesn't require time tracking (unless in a location where it is legally required).

Education assistance

Target's industry-leading education assistance benefit, Dream to Be, offers tuition-free programs to support your growth.

Market-leading pay

Target is a proud pay leader in retail and highly competitive with other large companies, providing equitable and competitive pay for all.

Team Target discount

Team members get a 10% discount at all Target stores and Target.com, along with 20% off wellness products and 20% off adult owned-brand apparel and accessories. Plus, get an additional 5% savings with a Target Circle Card. More about pay & benefits

Eligibility requirements may vary based on position, average hours worked, length of service and program requirements. Benefits are subject to change.

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here. A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Applied Data Sciences or Machine Learning teams, you'll be challenged to harness Target's impressive data breadth to build the algorithms that power solutions our partners in Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization rely on. Every Scientist on Target's Data Sciences team can expect modeling and data science, software/product development of highly performant code for model performance at scale. As the Lead Machine Learning Engineer - Merchandising, you will join a Data Sciences team responsible for creating and optimizing the data and models used to build a world-class merchandising product. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions. We will also expect you to understand best practice software design, participate in code reviews, and create a maintainable well-tested codebase with relevant documentation. At an organizational level, you may conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.