Lead ML Engineer – Applied ML, LLMs, ML Ops

Target

. Design, build, deploy, and maintain AI/ML applications supporting automation, insight, and action across core business workflows .

Posted 10/12/2026full-timeUnited StatesSenior💰 $132,000 - $286,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, building, and deploying AI/ML applications, with a strong focus on Python and modern frameworks like PyTorch and TensorFlow. Capable of translating complex business problems into scalable technical solutions while ensuring high standards of security, reliability, and maintainability.

Highest-signal resume keywords

AI/ML Application DevelopmentPython ProficiencyExperience with PyTorch and TensorFlowProduction System EngineeringTechnical Leadership and Mentorship

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML Application DevelopmentPython ProficiencyProduction System EngineeringData Pipeline DevelopmentModel Evaluation FrameworksSystem DesignApplication ArchitecturePerformance OptimizationVersion ControlCI/CD Practices

Soft Skills

Strong Communication SkillsCollaborative Team PlayerSelf-Driven and Results-OrientedMentorship AbilityProblem-Solving

Tools & Technologies

PyTorchTensorFlowLangChainLlamaIndexSemantic KernelCloud ML PlatformsObservability ToolsContainersOrchestration TechnologiesPrompt Orchestration

Certifications & Qualifications

MS in Computer ScienceMS in Machine LearningMS in Artificial IntelligenceMS in Applied Mathematics

Industry Keywords

AI EngineeringMachine LearningDeep LearningIntelligent AutomationData-Intensive ApplicationsProduction DeploymentTechnical DirectionCross-Functional CollaborationEnterprise StandardsContinuous Learning

Tech Stack

Tools & technologies

CloudPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, build, deploy, and maintain AI/ML applications supporting automation, insight, and action across core business workflows
Work closely with Data Scientists, engineers, product partners, platform teams, security teams, and business stakeholders
Turn ambiguous business problems into practical, scalable technical solutions
Provide hands-on technical leadership for AI engineering initiatives
Contribute to architecture and design decisions
Evaluate appropriate models, frameworks, and tools
Write maintainable, production-quality code
Establish engineering practices across development, testing, deployment, observability, documentation, and ongoing support
Ensure AI applications are secure, reliable, maintainable, and aligned with enterprise standards
Partner with senior engineers and engineering leaders to shape technical approaches, identify implementation risks, resolve roadblocks, and evolve reusable AI engineering patterns
Stay current with AI, machine learning, LLMs, agentic systems, and modern software engineering practices
Deliver production-grade AI applications that create measurable business value and raise the broader team’s technical quality and capability

Requirements

What you’ll need

4-year degree in Quantitative disciplines (Science, Tech, Engineering, Mathematics) or equivalent industry experience required
MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics or a related technical field preferred
5+ years of hands-on software engineering experience, including experience building and operating production systems
Strong experience developing AI/ML applications, including LLM-powered applications, agentic systems, applied machine learning solutions, data-intensive applications, or intelligent automation capabilities
Strong proficiency with Python and experience with modern AI/ML or deep learning frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Semantic Kernel, or similar tools
Experience working with model APIs, prompt orchestration, agent development patterns, 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 strategy, performance optimization, and production deployment considerations for AI systems
Experience building scalable, maintainable, and well-tested services, APIs, data pipelines, applications, or platforms
Experience with version control, CI/CD, code review practices, documentation, operational monitoring, and production support
Ability to translate ambiguous business problems into clear technical approaches and collaborate with cross-functional partners
Strong communication skills for explaining technical concepts to engineers, Data Scientists, product partners, business stakeholders, and leaders
Ability to mentor engineers, contribute to technical direction, and raise engineering-practice quality
Self-driven and results-oriented, with strong ownership, sound judgment, and ability to move quickly while maintaining high technical standards
Collaborative team player committed to continuous learning, knowledge sharing, and building reliable AI systems
Work duties cannot be performed outside the country of the primary work location unless otherwise prescribed by Target

Benefits

Comp & perks

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