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

Senior AI/ML Engineer within Target Data Sciences will design, implement, and deploy machine learning solutions to build and optimize guest audiences for highly personalized offers, collaborating across product, engineering, marketing, and analytics. Based in Brooklyn Park, MN with a hybrid work arrangement, the role offers a salary range of USD 98,000 to 176,000 per year.

Responsibilities

• Partner with cross-functional teams in product, engineering, marketing, and analytics to define strategy, lead experiments, and ensure personalization yields measurable impact for guests and the business.
• Design, implement, and optimize machine learning solutions in production environments.
• Apply best practice software design, participate in code reviews, and maintain a well-tested codebase with proper documentation.
• Lead training sessions, present work to both technical and non-technical peers and leaders, and translate business priorities into requirements and scalable solutions.
• Contribute to a Data Sciences team responsible for creating and maintaining audiences for highly personalized guest offers.

Requirements

• A four-year degree in quantitative fields (Science, Technology, Engineering, Mathematics) or equivalent experience.
• Master of Science in Computer Science, Applied Mathematics, Statistics, Physics, or equivalent industry experience.
• Three or more years of end-to-end machine learning application development including data pipelines, model optimization, deployment, and API design.
• Experience deploying machine learning algorithms into production environments.
• Strong proficiency in Python programming.
• Experience with ML frameworks such as PyTorch, TensorFlow, XGBoost, scikit-learn, and ONNX.
• Extensive experience with one or more cloud ML services such as GCP Vertex AI, Azure ML, or SageMaker.
• Experience using distributed training frameworks like Spark, Ray, or TensorFlow Distributed.
• Experience with serving frameworks such as TorchServe, TensorFlow Serving, or Serving/FastAPI.
• Solid understanding of Big Data technologies, particularly the Hadoop ecosystem (Spark, Kafka, Hive, etc.).
• Experience creating 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 machine learning solutions at scale.
• Excellent communication skills with the ability to convey data-driven narratives through appropriate visualizations, graphs, and storytelling.
• Self-driven and results-oriented, capable of meeting tight timelines.
• Motivated team player with the ability to collaborate effectively across a global team.

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 (medical, vision, dental, life insurance)
• 401(k)
• Employee discount
• Short-term disability
• Long-term disability
• Paid sick leave
• Paid national holidays
• Paid vacation
• Education benefits

About You

• A four-year degree in quantitative disciplines or equivalent experience.
• Master of Science in Computer Science, Applied Mathematics, Statistics, Physics, or related field, or equivalent industry experience.
• Three or more years of end-to-end machine learning application development including data pipelines, model optimization, deployment, and API design.
• Experience deploying machine learning algorithms into production environments.
• Strong Python programming skills.
• 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 with distributed training frameworks (Spark, Ray, TensorFlow Distributed).
• Experience with serving frameworks (TorchServe, TensorFlow Serving, FastAPI).
• Good understanding of Big Data technologies in the Hadoop ecosystem (Spark, Kafka, Hive).
• Experience building 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 present data-driven stories using visualizations and narratives.
• Self-motivated, results-oriented, able to meet tight timelines.
• Motivated, collaborative team player capable of working with a global team.