Target is looking to hire a Machine Learning Engineer to design, build, and scale high-performance on-demand model scoring and publishing applications that power decision-making across the enterprise. This role will focus on developing resilient, low-latency pipelines and services that deliver accurate forecasts at scale by leveraging modern distributed technologies to turn complex models into reliable, production-grade insights.
Requirements
- Demonstrated proficiency in Python, Java, or Scala programming
- Experience in end-to-end Machine Learning application development including data pipelining, model optimization, deployment and API design
- Experience with ML frameworks such as PyTorch, TensorFlow, XGBoost, and Scikit-learn
- Experience with cloud ML services such as Vertex AI, Azure ML, or SageMaker
- Familiarity with containerized technologies like Docker or Kubernetes
- Experience with software version control (e.g., Git) and unit/integration testing frameworks (e.g., PyTest, JUnit, ScalaTest)
- Strong commitment to writing high-quality, maintainable and well-tested code with clear documentation ensuring reliability, scalability and long-term sustainability in production systems
Responsibilities
- design, build, and scale high-performance on-demand model scoring and publishing applications
- develop resilient, low-latency pipelines and services that deliver accurate forecasts at scale
- leverage modern distributed technologies
- turn complex models into reliable, production-grade insights
- apply best practices in software design
- contribute to code reviews
- develop a maintainable, well-tested, and well-documented codebase
Other
- 4-year degree in a quantitative discipline (Computer Science, Technology, Engineering, Mathematics) or equivalent work experience
- Excellent communication skills with the ability to clearly tell data-driven stories through appropriate visualizations, graphs, and narratives
- Self-driven and results-oriented, with the ability to deliver against deadlines
- Motivated team player with the ability to collaborate effectively across a global team
- This position will operate as a Hybrid/Flex for Your Day work arrangement
