Target is hiring a Lead Machine Learning Engineer to design, implement, and optimize production machine learning solutions that power personalized recommendations for millions of guests on Target.com and the Target mobile app. You'll join a global in-house Tech and Data Sciences team of more than 5,000 software engineers, applied data scientists, ML engineers and product managers, and be part of a Data Sciences team specifically focused on personalized recommendations.

What You'll Do

Design, implement, and optimize production machine learning solutions.
Create personalized recommendations on Target.com and the Target mobile app.
Understand best practice software design and participate in code reviews.
Create a maintainable, well-tested codebase with relevant documentation.
Conduct training sessions and present work to technical and non-technical peers and leaders.
Build knowledge on business priorities and strategic goals to inform requirements and solutions.
Work in partnership with data scientists, software engineers, and product managers to translate business requirements into machine learning solutions at scale.
Mentor junior team members in ML skillset and career development.

What We're Looking For

A 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience.
5+ years of experience in end-to-end Machine Learning application development, including data pipelining, model optimization, deployment, and API design.
High proficiency programming in Python.
Experience with ML frameworks such as PyTorch, TensorFlow, xgboost, sklearn, and ONNX.
Extensive experience with one or more cloud ML services such as Vertex AI, Azure ML, or SageMaker.
Experience using distributed training frameworks like Spark, Ray, or TensorFlow Distributed.
Experience with serving frameworks such as TorchServe, TensorFlow Serving, or FastAPI.
A good understanding of Big Data technologies, specifically Hadoop, Kafka, and Spark.
Experience creating and maintaining CI/CD pipelines for automated model deployment and testing.
Excellent communication skills with the ability to clearly tell data-driven stories.
A self-driven, results-oriented approach with the ability to meet tight timelines.
Motivation and the ability to collaborate effectively as a team player across a global team.

Nice to Have

An MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience.
A PhD in Computer Science, Applied Mathematics, Statistics, Physics or a related quantitative field.
Proficiency in Java.

Technical Stack

Languages: Python
ML Frameworks: PyTorch, TensorFlow, xgboost, sklearn, ONNX
Cloud ML: Vertex AI, Azure ML, SageMaker
Distributed Training: Spark, Ray, TensorFlow Distributed
Serving Frameworks: TorchServe, TensorFlow Serving, FastAPI
Big Data: Hadoop, Kafka, Spark

Team & Environment

You will join a global in-house Tech and Data Sciences team of more than 5,000 software engineers, applied data scientists, ML engineers, and product managers. You'll be part of a Data Sciences team specifically responsible for personalized recommendations, working in a culture focused on experimentation, continuous learning, agile practices, and leveraging open-source software.