This Senior AI/ML Engineer role is part of Target Data Sciences, based in Brooklyn Park, MN with a hybrid work arrangement. The position centers on designing, implementing, and deploying machine learning solutions to build and optimize audiences for highly personalized offers, collaborating across product, engineering, marketing, and analytics disciplines. The role offers a salary range of USD 98,000 to 176,000 per year and requires an MS degree along with a minimum of three years of relevant experience.
Responsibilities
- Collaborate with cross functional partners in product, engineering, marketing, and analytics to define strategy, lead experimentation, and ensure personalization delivers measurable impact for guests and the business.
- Design, implement, and optimize machine learning solutions in production environments.
- Apply best practices in software design, participate in code reviews, and maintain a well-tested codebase with thorough documentation.
- Lead training sessions and present work to both technical and non-technical audiences, translating business priorities into requirements and ML solutions.
- Join a Data Sciences team responsible for creating and maintaining audiences for highly personalized offers to guests.
Requirements
- Minimum 4-year degree in quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience; MS in Computer Science, Applied Mathematics, Statistics, Physics, or related field.
- At least 3 years of end-to-end ML application development, including data pipelining, model optimization, deployment, and API design.
- Experience deploying machine learning algorithms into production environments.
- 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.
- Strong understanding of Big Data technologies within the Hadoop ecosystem (Spark, Kafka, Hive, etc.).
- Experience creating and maintaining CI/CD pipelines for automated model deployment and testing.
- Ability to work with applied data scientists, software engineers, and product managers to translate business requirements into scalable ML solutions.
- Excellent communication skills with the ability to convey data-driven insights through visuals, graphs, and narratives.
- 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
- Apache 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) retirement savings plan
- Employee discount
- Short-term disability
- Long-term disability
- Paid sick leave
- Paid national holidays
- Paid vacation
- Education benefits
About You
Candidates should hold a MS in a quantitative field (or an equivalent combination of degree and experience) and possess at least three years of end-to-end ML development, including data pipelining, model optimization, deployment, and API design. The role requires experience deploying ML models to production, strong Python skills, familiarity with major ML frameworks, and hands-on use of cloud ML services. Knowledge of distributed training, serving frameworks, Big Data technologies, and CI/CD is essential, along with the ability to partner with applied data scientists, software engineers, and product managers to deliver scalable ML solutions. Excellent communication, a data-driven storytelling ability, self-direction, and collaborative mindset for working with a global team are expected.
