Sr Machine Learning Engineer - Marketing and Corporate Systems (ML Ops)

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.