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Target
Target
H1B Visa SponsorB2CeCommerceRetail
Target is a major American retailer serving consumers through stores and digital commerce. Founded in 1946, the company combines retail, eCommerce, and consumer-focused experiences with an emphasis on value, design, innovation, and convenient shopping. Target’s large organization brings together teams working across the retail business and supports communities through responsible corporate practices, environmental stewardship, ethical operations, and charitable giving.
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Senior Lead Machine Learning Engineer, Applied AI and LLMs

Lead the development of production AI and machine learning applications for Target’s retail business. Provide hands-on technical direction across LLMs, applied ML, system architecture, deployment, and operations.

USUnited StatesCACaliforniaMNMinnesota
$132,000 – $286,000 / year
HybridFull-timeSeniorEnglish RequiredMachine Learning Engineer
CloudPythonPyTorchTensorflow

Description

  • Build and operate AI and machine learning applications that automate workflows and deliver useful insights.
  • Collaborate with data scientists, engineering, product, platform, security, and business teams.
  • Translate loosely defined business needs into practical, scalable technical solutions.
  • Lead AI engineering work through hands-on technical contributions.
  • Help guide architecture and design decisions.
  • Assess and select suitable models, frameworks, and tools.
  • Develop maintainable code that meets production standards.
  • Set practices for development, testing, deployment, observability, documentation, and ongoing support.
  • Keep AI applications secure, dependable, maintainable, and consistent with enterprise standards.
  • Work with senior engineers and leaders to define technical approaches, surface implementation risks, clear obstacles, and develop reusable AI engineering patterns.
  • Keep up with developments in AI, machine learning, LLMs, agent-based systems, and software engineering.
  • Deliver production-ready AI applications with measurable business impact while strengthening the team’s technical skills and practices.

Requirements

  • A four-year degree in a quantitative field such as science, technology, engineering, or mathematics, or equivalent industry experience.
  • A master’s degree in computer science, machine learning, artificial intelligence, applied mathematics, or a related technical field is preferred.
  • At least five years of hands-on software engineering experience, including building and operating production systems.
  • Strong experience developing AI and ML applications, such as LLM-powered products, agent-based systems, applied ML solutions, data-intensive applications, or intelligent automation.
  • Proficiency in Python and experience with modern AI, ML, or deep learning frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, or Semantic Kernel.
  • Experience with model APIs, prompt orchestration, agent development, retrieval-augmented generation, evaluation frameworks, observability tools, cloud ML platforms, containers, or orchestration technologies.
  • Strong understanding of system design, application architecture, model and framework tradeoffs, experimentation, evaluation, performance optimization, and production deployment for AI systems.
  • Experience building scalable, maintainable, well-tested services, APIs, data pipelines, applications, or platforms.
  • Experience with version control, CI/CD, code review, documentation, operational monitoring, and production support.
  • Ability to turn unclear business needs into defined technical approaches and work effectively with cross-functional partners.
  • Strong communication skills, including explaining technical concepts to engineers, data scientists, product partners, business stakeholders, and leaders.
  • Ability to mentor engineers, help set technical direction, and improve engineering practices.
  • Self-directed and results-oriented, with strong ownership, sound judgment, and the ability to move quickly while maintaining high technical standards.
  • Collaborative approach, with commitment to continued learning, knowledge sharing, and building reliable AI systems.
  • Work must be performed within the country of the primary work location unless Target specifies otherwise.

Benefits

  • Comprehensive health programs that may include medical, vision, dental, life insurance, and more.
  • 401(k) plan.
  • Employee discount.
  • Short-term disability coverage.
  • Long-term disability coverage.
  • Paid sick leave.
  • Paid national holidays.
  • Paid vacation.
  • Financial, education, and well-being benefits.

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