AI/ML Engineer - RecSys (ML Ops)

Target•Brooklyn Park, MN

1d•$75,400 - $135,700•Hybrid

About The Position

Working at Target means helping all families discover the joy of everyday life. 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 an AI Engineer, you will join a Data Sciences team responsible for creating personalized recommendations on Target.com and the Target App. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions and the platforms supporting them. We will 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 will work in partnership with data scientists, engineers, and product managers to understand the business requirements and build solutions to meet business needs. Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

Requirements

BS, MS or PhD in Computer Science, Applied Mathematics, Statistics, Physics, equivalent work or industry experience
1 plus year of applied machine learning application development including data pipelining, model optimization, deployment/ML Ops and API design
Strong programming in Python, Java, SQL and experience with ML frameworks such as PyTorch, TensorFlow, XGBoost and sklearn
Experience with cloud ML services such as Vertex AI, Azure ML or AWS Sagemaker
Experience with containerized technologies like Docker and Kubernetes
Experience with PySpark
Experience with software design on Linux/Mac
Experience with software version control such as Git and software test coverage practices/frameworks such as PyTest or JUnit
Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs and narratives
Self-driven and results oriented; able to meet deadlines
Motivated, team player with ability to collaborate effectively across a global team

Responsibilities

Designing, implementing, and optimizing production machine learning solutions and the platforms supporting them.
Understanding best practice software design.
Participating in code reviews.
Creating a maintainable well-tested codebase with relevant documentation.
Working in partnership with data scientists, engineers, and product managers to understand the business requirements and build solutions to meet business needs.