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UPS

Lead AI/ML Engineering (Flex)

UPS is hiring a Lead AI/ML Engineering (Flex). It pays $109k-$231k a year and Level rates it ; you can apply on UPS.

Level's read on this job

  • Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
  • UPS mentions visa sponsorship in this posting.
  • Tools and skills the posting cites include prompt engineering, RAG and LLM integration.
  • Level lists 2,000+ other open roles at UPS.
  • The role was posted in the last few days.

AI in this role

prompt-engineeringragllm-integrationai-agentsml-opsai-evaluationnlpai-safety

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Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow—people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.

Job Description:

THIS POSITION IS HYBRID AND WILL REQUIRE CANDIDATES TO WORK IN THE FOLLOWING UPS IT LOCATIONS: NEW JERSEY, ATLANTA, MARYLAND, AND KENTUCKY OFFICE 3 DAYS A WEEK


This position provides technical and delivery leadership for teams developing enterprise AI, analytics, and intelligent software solutions. The role leads the design, development, integration, and production deployment of capabilities that combine generative AI, machine learning, enterprise data, analytics, and agentic technologies to solve complex business problems and accelerate decision-making.

The position partners across Business, Product, Architecture, Engineering, Data Science, and Data Engineering to translate business needs into scalable, secure, and reusable solutions. The role establishes engineering patterns and best practices for AI orchestration, data integration, evaluation, testing, observability, security, and production operations.

This position serves as a technical lead and subject matter expert, drives adoption of modern AI and software engineering practices, leads complex initiatives from concept through production, and mentors engineering talent.

Responsibilities

  • Leads the design and implementation of enterprise AI, analytics, and intelligent software solutions across cloud and distributed environments.
  • Translates complex business problems into scalable solutions using generative AI, agentic AI, machine learning, analytics, and automation.
  • Leads development of AI agents and intelligent applications, including LLM integration, orchestration, retrieval-augmented generation (RAG), semantic retrieval, enterprise data, and tool integration.
  • Establishes reusable architectures, frameworks, engineering patterns, and components that accelerate delivery across business domains and use cases.
  • Collaborates across Business, Product, Architecture, Engineering, Data Science, Data Engineering, UX, and Security to deliver enterprise AI capabilities.
  • Leads integration of structured and unstructured enterprise data into AI, analytics, and machine learning solutions.
  • Evaluates and applies appropriate AI and ML technologies, balancing generative AI, predictive modeling, traditional machine learning, and deterministic approaches based on business requirements.
  • Establishes AI evaluation and testing practices for grounding, accuracy, relevance, reliability, performance, regression testing, and production monitoring.
  • Leads adoption of cloud-native architectures, APIs, data pipelines, and integration patterns supporting scalable AI and analytics workloads.
  • Champions responsible and secure AI practices, including data governance, identity and access, privacy, traceability, auditability, and appropriate human oversight.
  • Drives engineering excellence through CI/CD, DevSecOps, MLOps/LLMOps, automated testing, observability, deployment automation, and production operations.
  • Leads complex technical initiatives, manages dependencies and risks, resolves technical roadblocks, and provides technical guidance across project teams.
  • Partners with business and product stakeholders to prioritize capabilities based on business value, scalability, reuse, and measurable outcomes.
  • Acts as a technical leader and mentor, developing engineering talent and promoting modern AI and software engineering practices.

Qualifications

  • 8+ years of experience across the Software Development Life Cycle (SDLC) designing, building, deploying, and operating enterprise software, data, analytics, or AI solutions.
  • Demonstrated experience leading the development and production deployment of generative AI, agentic AI, machine learning, or intelligent applications.
  • Experience with LLMs, RAG, AI agents, orchestration, prompt engineering, semantic retrieval, and AI evaluation.
  • Experience designing scalable cloud-native architectures, APIs, data pipelines, and enterprise integrations supporting AI solutions.
  • Strong understanding of AI engineering practices, including grounding, evaluation, observability, performance, security, responsible AI, and MLOps/LLMOps.
  • Experience applying ML and analytical techniques such as NLP, classification, regression, forecasting, and predictive modeling.
  • Experience with Agile development, CI/CD, DevSecOps, automated testing, and production operations.
  • Demonstrated ability to establish reusable engineering patterns, lead complex technical initiatives, mentor engineering talent, and collaborate across technical and business teams.
  • Strong written and verbal communication skills with the ability to translate complex technical concepts into business outcomes.
  • Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related technical discipline, international equivalent, or equivalent job experience.

Additional Information

  • Job Grade: 303

Pay Range:

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $108,600/year to 231,084/year. Pay is based on several factors including but not limited to, market location and may vary depending on job-related knowledge, skills, and education/training and a candidate’s work experience. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance. Hired applicants may be eligible for Medical/prescription drug coverage, Dental coverage, Vision coverage, Flexible Spending Account, Health Savings Account, Dependent Care Flexible Spending Account, Basic and Supplemental Life Insurance & Accidental Death and Dismemberment, Disability Income Protection Plan, Employee Assistance Program, 401(k) retirement program, Vacation, Paid Holidays and Personal time, Paid Sick and Family and Medical Leave time as required by law, and Discounted Employee Stock Purchase Program.


Employee Type:

Permanent

UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

Other Criteria:

Employer will sponsor visas for specific positions. UPS is an equal opportunity employer. UPS does not discriminate on the basis of race/color/religion/sex/national origin/veteran/disability/age/sexual orientation/gender identity or any other characteristic protected by law.

How we rate this

Lead AI/ML Engineering (Flex) at UPS rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGLLM IntegrationAI agentsML OpsAI EvaluationNLPAI Safety

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$109k
Typical machine learning engineer job
$198k

This posting starts 45% below the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How have you integrated a large language model into a production application?
  4. How do you decide when an AI agent can act on its own versus asking for approval first?
  5. How do you monitor a model once it's live, and how do you know it needs retraining?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, RAG, LLM Integration, AI agents, and ML Ops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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