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

TargetBrooklyn Park, MN
$98,000 - $176,000Hybrid

About The Position

A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Applied Data Sciences or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization rely on. Every Scientist on Target’s Data Sciences team can expect modeling and data science, software/product development of highly performant code for model performance at scale. As a Sr AI/ML Engineer, you will join a Data Sciences team responsible for implementing solutions that create and maintain audiences for highly personalized offers to our Guests. You will collaborate with cross-functional partners in product, engineering, marketing, and analytics to define strategy, lead experimentation, and ensure that personalization drives measurable impact for our guests and business. You will play crucial role in designing, implementing, and optimizing the machine learning solutions in production. We will also expect you to understand best-practice software design, participate in code reviews, create a maintainable and well-tested codebase with relevant documentation. At an organizational level, you will conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.

Requirements

  • 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
  • MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience
  • 3 plus years' of experience in 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 programming in Python
  • Experience with ML frameworks such as Pytorch, TensorFlow, xgboost, sklearn and ONNX
  • Extensive experience with one or more cloud ML service such as GCP Vertex AI, Azure ML or Sagemaker
  • Experience using distributed training frameworks like Spark, Ray, TensorFlow Distributed
  • Experience with serving frameworks such as TorchServe/TensorFlow or Serving/FastAPI
  • Good understanding of Big Data tech, specifically Hadoop ecosystem – Spark, Kafka, Hive, etc.
  • Experience creating and maintaining CI/CD pipelines for automated model deployment and testing
  • Work in partnership with applied data scientists, software engineers and product managers to understand the business requirements - translate to machine learning solutions at scale
  • Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
  • Self-driven and results oriented - able to meet tight timelines
  • Motivated, team player with ability to collaborate effectively across global team
  • Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives

Responsibilities

  • Implementing solutions that create and maintain audiences for highly personalized offers to our Guests.
  • Collaborating with cross-functional partners in product, engineering, marketing, and analytics to define strategy, lead experimentation, and ensure that personalization drives measurable impact for our guests and business.
  • Designing, implementing, and optimizing the machine learning solutions in production.
  • Understanding best-practice software design, participating in code reviews, creating a maintainable and well-tested codebase with relevant documentation.
  • Conducting training sessions, presenting work to technical and non-technical peers/leaders, building knowledge on business priorities/strategic goals and leveraging this knowledge while building requirements and solutions for each business need.

Benefits

  • Comprehensive health benefits and programs, which may include 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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