AI/ML Engineer Sr (mid-career)

Lockheed Martin is a leading aerospace and defense company that focuses on innovative solutions in data and artificial intelligence. They are seeking a Senior AI/ML Engineer to develop and implement AI and machine learning solutions that drive business improvements and support data-based decision-making within the organization.

Responsibilities:

• Conducting experiments and 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 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
• Hands‑on experience with large‑language‑model APIs, prompt engineering, Retrieval‑Augmented Generation (RAG), and agentic orchestration tools (e.g., LangChain, ReAct)
• Demonstrated ability to lead multiple projects simultaneously, define scope, set milestones, and deliver results independently
• Excellent written and verbal communication skills; ability to present technical concepts to executive audiences and produce clear documentation
• 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