Lead ML Engineer — Scalable AI & Production Systems

Target

Brooklyn Park (MN)

Hybrid

USD 132,000 - 286,000

Full time

5 days ago
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Job summary

Target's Advanced AI team is hiring a Lead ML Engineer to design, build, and deploy AI/ML applications that drive business value across core workflows. Collaborate with data scientists, engineers, product partners, platform and security teams to turn ambiguous problems into scalable technical solutions.

You will provide hands-on technical leadership, shape architecture, evaluate models and tools, and ensure secure, reliable production deployments.

Qualifications

  • 4-year degree in quantitative disciplines or equivalent experience.
  • 5+ years of hands-on software engineering experience.
  • Strong experience developing AI/ML applications including LLM-powered solutions.
  • Proficiency with Python and ML frameworks such as PyTorch or TensorFlow.
  • Experience with model APIs, prompt orchestration, and cloud ML platforms.
  • Understanding of system design, production deployment, and observability for AI systems.
  • Experience with version control, CI/CD, and production support.
  • Ability to translate business problems into actionable technical solutions.
  • Strong communication and mentoring abilities.

Responsibilities

  • Design, build, deploy, and maintain AI/ML applications that support automation and insight.
  • Collaborate with data scientists, engineers, product partners, and stakeholders.
  • Evaluate models, frameworks, and tools; write production-quality code.
  • Ensure security, reliability, and maintainability of AI systems.
  • Lead engineering practices and contribute to reusable AI patterns.

Skills

Python
AI/ML apps
LLM-powered
LangChain
TensorFlow
PyTorch
Cloud ML
APIs & orchestration

Education

4-year degree in Quantitative disciplines

Tools

PyTorch
TensorFlow
LangChain
LlamaIndex
Semantic Kernel

Job description

Target's Advanced AI team is hiring a Lead ML Engineer to design, build, and deploy AI/ML applications that drive business value across core workflows. Collaborate with data scientists, engineers, product partners, platform and security teams to turn ambiguous problems into scalable technical solutions.

You will provide hands-on technical leadership, shape architecture, evaluate models and tools, and ensure secure, reliable production deployments.

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