Sr Machine Learning Engineer - Marketing and Corporate Systems; ML Ops

JOIN TARGET AS A SR AI/ML ENGINEER - MARKETING TECH

The pay range is $98,000.00 - $.

Pay is based on several factors which vary based on position. These include labor markets and may include education, work experience, and certifications. In addition to pay, Target cares about and invests in team members 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

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. 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 a Sr AI/ML Engineer, you will join a Data Sciences team responsible for implementing solutions that create and maintain audiences for highly personalized offers to our Guests. You will collaborate with cross‑functional partners in product, engineering, marketing, and analytics to define strategy, lead experimentation, and ensure that personalization drives measurable impact for our guests and business.

You will play a crucial role in designing, implementing, and optimizing machine learning solutions in production. We will also expect you to understand best‑practice software design, participate in code reviews, create a maintainable and well‑tested codebase with relevant documentation. At an organizational level, you will conduct training sessions, present work to technical and non‑technical peers and leaders, build knowledge on business priorities and strategic goals, and leverage this knowledge while building requirements and solutions for each business need.

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

• 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
• 3+ years of experience in end‑to‑end Machine Learning application development including data pipelining, model optimization, deployment, and API design
• Experience deploying Machine Learning algorithms into production environments
• Highly proficient programming in Python
• Experience with ML frameworks such as PyTorch, Tensor Flow, XGBoost, scikit‑learn, and ONNX
• Extensive experience with one or more cloud ML services such as GCP Vertex AI, Azure ML, or Sage Maker
• Experience using distributed training frameworks like Spark, Ray, Tensor Flow Distributed
• Experience with serving frameworks such as Torch Serve, Tensor Flow Serving or FastAPI
• Good understanding of Big Data tech, specifically Hadoop ecosystem – Spark, Kafka, Hive, etc.
• Experience creating and maintaining CI/CD pipelines for automated model deployment and testing
• Work in partnership with applied data scientists, software engineers, and product managers to understand business requirements and translate them to machine learning solutions at scale
• Excellent communication skills with the ability to clearly tell data‑driven stories through appropriate visualizations, graphs, and narratives
• Self‑dri…