Machine Learning Engineer - Demand Forecasting
Job Description
Target, one of America's leading retailers, is seeking a Machine Learning Engineer to join their Demand Forecasting Engine (DFE) team. This role sits at the crucial intersection of advanced data science and large-scale distributed systems, where you'll be responsible for designing and implementing high-performance machine learning solutions that drive enterprise-wide decision-making.
As a Machine Learning Engineer, you'll be working on building and scaling sophisticated model scoring and publishing applications that power Target's demand forecasting capabilities. The role combines technical expertise in ML frameworks, distributed systems, and software engineering best practices with the business-critical task of delivering accurate forecasts at scale.
The position offers a competitive salary range of $73,200 - $131,700, along with comprehensive benefits including health coverage, 401(k), and various insurance options. Working in a hybrid model, you'll have the flexibility to work both from Target's headquarters and remotely, fostering a balanced work environment.
The ideal candidate will bring strong technical skills in Python, Java, or Scala, along with experience in ML frameworks and cloud services. You'll be joining a collaborative, global team where your contributions will directly impact Target's ability to optimize its operations and better serve its customers.
This role presents an excellent opportunity for a mid-level engineer looking to work with cutting-edge ML technologies while solving real-world business challenges at scale. You'll be part of Target's mission to help families discover the joy of everyday life while working on technically challenging problems in a supportive, growth-oriented environment.
Responsibilities For Machine Learning Engineer - Demand Forecasting
- Design, build, and scale high-performance on-demand model scoring and publishing applications
- Develop resilient, low-latency pipelines and services
- Deliver accurate forecasts at scale
- Apply best practices in software design
- Contribute to code reviews
- Develop maintainable, well-tested, and well-documented codebase
- Collaborate with data scientists, engineers, and product managers
- Translate business requirements into scalable, production-ready solutions
Requirements For Machine Learning Engineer - Demand Forecasting
- 4-year degree in a quantitative discipline (Computer Science, Technology, Engineering, Mathematics) or equivalent work experience
- Demonstrated proficiency in Python, Java, or Scala programming
- Experience in end-to-end Machine Learning application development
- 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 and unit/integration testing frameworks
- Strong commitment to writing high-quality, maintainable code
- Understanding of the end-to-end model lifecycle
- Excellent communication skills
- Self-driven and results-oriented
- Ability to collaborate effectively across a global team
Benefits For Machine Learning Engineer - Demand Forecasting
- Health benefits (medical, vision, dental)
- Life insurance
- 401(k)
- Employee discount
- Short term disability
- Long term disability
- Paid sick leave
- Paid national holidays
- Paid vacation
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