AI/ML Engineer Sr (mid-career)

Lockheed MartinChicago, WA
Remote

About The Position

The Lockheed Martin Data & AI Enablement – Advanced Solutions team supporting Rotary & Mission Systems (RMS) is responsible for developing strategies and implementing integrated, cross‑functional solutions that transform operations through data‑based decisions that deliver business‑based outcomes. Our AI team is at the forefront of the digital transformation, building artificial‑intelligence and machine‑learning solutions that drive tangible business improvements. A Senior AI/ML Engineer will be a hands‑on practitioner tasked with conducting experiments, building production‑grade solutions, and partnering with stakeholders and analysts to identify high‑impact opportunities within large structured and unstructured data sets. The role applies and/or develops advanced technologies, scientific principles, and AI techniques to model complex business problems, discover insights, and provide actionable recommendations while guiding the team’s technical direction and mentoring junior engineers.

Requirements

  • Bachelor’s (minimum) or Master’s degree in Computer Science, AI/ML, Electrical/Computer Engineering, or a related field
  • 3 + years of hands‑on AI/ML engineering experience with a proven record of delivering production AI solutions
  • Strong proficiency in Python

Nice To Haves

  • Deep knowledge of MLOps: model versioning, monitoring, Docker/Kubernetes, CI/CD pipelines (GitLab, OpenShift)
  • Design and deployment of agentic systems – multi‑agent orchestration, hierarchical reinforcement learning, autonomous pipelines
  • Experience with multi‑model system design – integrating vision, language, and reinforcement‑learning models into cohesive products
  • Large‑scale AI platform engineering – scaling AI services across cloud environments, handling high‑throughput inference workloads
  • Knowledge‑graph & semantic search expertise (ontologies, SPARQL, embedding‑driven graphs)
  • Ability to evaluate emerging AI tools, author best‑practice guidelines, and drive adoption across the team
  • Provide mentorship and technical guidance to junior developers, helping them grow their AI/ML skills, adopt best‑practice coding standards, and contribute effectively to team projects
  • Enable business users by translating technical solutions into clear, actionable insights, offering training and self‑service tools so they can independently explore data and make data‑driven decisions
  • Proven success leading cross‑functional teams and influencing technical roadmaps
  • Research orientation – continuously monitor emerging AI trends, produce impact analyses, and share insights with the broader organization

Responsibilities

  • Conducting experiments
  • Building production-grade solutions
  • Partnering with stakeholders and analysts to identify high-impact opportunities within large structured and unstructured data sets
  • Applying and/or developing advanced technologies, scientific principles, and AI techniques to model complex business problems, discover insights, and provide actionable recommendations
  • Guiding the team’s technical direction
  • Mentoring junior engineers
  • Design and deployment of agentic systems – multi‑agent orchestration, hierarchical reinforcement learning, autonomous pipelines
  • Experience with multi‑model system design – integrating vision, language, and reinforcement‑learning models into cohesive products
  • Large‑scale AI platform engineering – scaling AI services across cloud environments, handling high‑throughput inference workloads
  • Knowledge‑graph & semantic search expertise (ontologies, SPARQL, embedding‑driven graphs)
  • Ability to evaluate emerging AI tools, author best‑practice guidelines, and drive adoption across the team
  • Provide mentorship and technical guidance to junior developers, helping them grow their AI/ML skills, adopt best‑practice coding standards, and contribute effectively to team projects
  • Enable business users by translating technical solutions into clear, actionable insights, offering training and self‑service tools so they can independently explore data and make data‑driven decisions
  • Proven success leading cross‑functional teams and influencing technical roadmaps
  • Research orientation – continuously monitor emerging AI trends, produce impact analyses, and share insights with the broader organization

Benefits

  • Medical
  • Dental
  • Vision
  • Life Insurance
  • Short-Term Disability
  • Long-Term Disability
  • 401(k) match
  • Flexible Spending Accounts
  • EAP
  • Education Assistance
  • Parental Leave
  • Paid time off
  • Holidays
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service