✦ Luna Orbit — AI & Machine Learning

Machine Learning Engineer - AI team

at Target

📍 7000 Target Pkwy N,NCD-0375 Brooklyn Park,MN 55445 Hybrid 💰 $75K – $135K USD / year Posted March 13, 2026
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Position Details

Salary $75K – $135K USD / year
Type Full-Time
Experience mid
Exp. Years Not specified
Education 4-year degree in Quantitative disciplines or equivalent work experience
Category AI & Machine Learning

About this role

This role involves designing, implementing, and optimizing machine learning solutions to enhance Target's personalized recommendations and data-driven initiatives.

Key Responsibilities

  • Create ML models
  • Optimize model lifecycle
  • Collaborate with data scientists
  • Deploy models using Docker and Kubernetes
  • Ensure production stability

Technical Overview

Utilizes Python, SQL, Docker, Kubernetes, and ML frameworks like PyTorch and TensorFlow to develop and deploy ML models in a hybrid environment.

Ideal Candidate

The ideal candidate is a data scientist or ML engineer with proficiency in Python and SQL, experienced in deploying machine learning models using Docker and Kubernetes, and familiar with ML frameworks like PyTorch and TensorFlow.

Must-Have Skills

PythonSQLDockerKubernetesGit

Nice-to-Have Skills

JavaPyTorchTensorFlowXGBoostScikit-learnLinuxMacPyTest

Tools & Platforms

GitPyTestDockerKubernetesLinuxMac

Required Skills

PythonJavaPyTorchTensorFlowXGBoostScikit-learnLinuxMacGitPyTestSQLDockerKubernetes

Hard Skills

PythonJavaPyTorchTensorFlowXGBoostScikit-learnLinuxMacGitPyTestSQLDockerDroneKubernetes

Soft Skills

problem-solvingcollaborationcommunicationanalytical thinkingadaptability

Industry & Role

Industry Retail / E-commerce / Data Science
Job Function Machine learning engineering for Target's AI initiatives

Keywords for Your Resume

PythonJavaPyTorchTensorFlowXGBoostScikit-learnLinuxMacGitPyTestSQLDockerKubernetesData ScienceMachine LearningAIModel lifecycleData ingestionFeature extractionModel trainingModel evaluation

Deal Breakers

Lack of experience with Python or SQL, No familiarity with Docker or Kubernetes, Unwilling to work in a hybrid environment, No experience with ML frameworks

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