Lead Machine Learning Engineer - Merchandising AI (ML Ops)

Target • Brooklyn Park, NC

2d • Hybrid

About The Position

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.

Requirements

• 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
• 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
• Self-driven, results-oriented and able to meet tight deadlines
• Motivated team player who thrives in a collaborative global environment

Nice To Haves

• Ability to mentor engineers and help establish engineering standards, architecture patterns, and best practices for AI/ML and cloud-native development.

Responsibilities

• Designing, implementing, and optimizing production machine learning solutions.
• Understanding best practice software design.
• Participating in code reviews.
• Creating a maintainable well-tested codebase with relevant documentation.
• Conducting training sessions.
• Presenting work to technical and non-technical peers/leaders.
• Building knowledge on business priorities/strategic goals and leveraging this knowledge while building requirements and solutions for each business need.
• Lead the development of agentic AI solutions that connect data, tools, APIs and business rules into end-to-end decisioning workflows.

Benefits

• Comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more
• 401(k)
• Employee discount
• Short term disability
• Long term disability
• Paid sick leave
• Paid national holidays
• Paid vacation

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree