Target Data Sciences is seeking a Senior Machine Learning Engineer to design, implement, and deploy ML solutions that power audiences for highly personalized offers. In a hybrid role based in Brooklyn Park, MN, you will collaborate across product, engineering, marketing, and analytics to translate business priorities into scalable ML systems for Marketing and Corporate Systems.
Responsibilities
- Work with cross-functional partners in product, engineering, marketing, and analytics to set strategy, run experiments, and ensure personalization drives measurable impact for guests and the business.
- Design, implement, and optimize ML solutions that operate in production environments.
- Apply best practices in software design, participate in code reviews, and maintain a well-tested codebase with proper documentation.
- Lead training sessions and present work to both technical and non-technical stakeholders, translating business priorities into effective requirements and solutions.
- Join a Data Sciences team focused on creating and maintaining audiences for highly personalized offers to guests.
Requirements
- Bachelor's degree in a quantitative field (Science, Technology, Engineering, Mathematics) or equivalent experience; MS in Computer Science, Applied Mathematics, Statistics, Physics, or related field is preferred.
- 3+ years of end-to-end machine learning application development, including data pipelining, model optimization, deployment, and API design.
- Experience deploying machine learning algorithms into production environments.
- Highly proficient in Python programming.
- Experience with ML frameworks such as PyTorch, TensorFlow, XGBoost, scikit-learn, and ONNX.
- Extensive experience with cloud ML services like GCP Vertex AI, Azure ML, or SageMaker.
- Experience using distributed training frameworks such as Spark, Ray, or TensorFlow Distributed.
- Experience with serving frameworks such as TorchServe, TensorFlow Serving, or FastAPI.
- Solid understanding of Big Data technologies, including the Hadoop ecosystem (Spark, Kafka, Hive, etc.).
- Experience building and maintaining CI/CD pipelines for automated model deployment and testing.
- Ability to collaborate with applied data scientists, software engineers, and product managers to translate business requirements into scalable ML solutions.
- Excellent communication skills with the ability to tell data-driven stories through visualizations, graphs, and narratives.
- Self-driven and results-oriented, capable of meeting tight deadlines.
- Motivated, team-oriented collaborator with the ability to work across global teams.
Technologies
- Python
- PyTorch
- TensorFlow
- XGBoost
- scikit-learn
- ONNX
- GCP Vertex AI
- Azure ML
- SageMaker
- Spark
- Ray
- TensorFlow Distributed
- TorchServe
- TensorFlow Serving
- FastAPI
- Hadoop
- Kafka
- Hive
- CI/CD pipelines
Benefits
- Health benefits including medical, vision, dental, and life insurance
- 401(k) plan
- Employee discount
- Short-term disability
- Long-term disability
- Paid sick leave
- Paid national holidays
- Paid vacation
- Education benefits
About You
Ideal candidates typically hold a MS in a quantitative field or equivalent experience and bring 3+ years of end-to-end ML development, including data pipelines, model optimization, deployment, and API design. You should have production deployment experience, strong Python proficiency, and hands-on work with major ML frameworks, cloud ML services, distributed training, serving solutions, and big data tools. Clear communication, a collaborative mindset, and the ability to work toward business goals at scale are essential.
