AI/ML Engineer- Early Career
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. An RMS AI/ML Engineer (Level 1) will be a hands-on practitioner tasked with conducting experiments, building solutions, and partnering with stakeholders and analysts to identify new opportunities utilizing large sets of structured and unstructured data. The role will apply advanced technologies and scientific principles to uncover meaningful patterns in ambiguous problem spaces, model complex business challenges, and deliver actionable insights. 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. An 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.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, AI/ML, or a related discipline.
- Proficiency in Python – write clean, well-documented code and explain your logic.
- Knowledge of the data-science lifecycle, big-data concepts, deep-learning fundamentals, and reinforcement-learning ideas.
- Basic awareness of Generative AI capabilities such as large-language models (LLMs)
- Demonstrated initiative and research mindset – comfortable navigating documentation, exploring new tools, and proposing ideas with minimal supervision.
- Strong problem-solving and communication skills; able to work with internal customers to gather requirements and provide clear status updates.
- Must be a US Citizen
Nice To Haves
- Experience with LLM frameworks or APIs (e.g., LangChain, OpenAI, Cohere).
- Exposure to MLOps fundamentals: CI/CD pipelines, model versioning, monitoring, Docker/Kubernetes.
- Knowledge-graph or ontology work (SPARQL, embeddings, graph-based feature engineering).
- Familiarity with cloud platforms (AWS, Azure, GCP) and OpenShift.
- Ability to quickly absorb new tools, applications, or approaches from documentation or public repositories and contribute ideas to the team.
- Research-oriented mindset – conducting industry/academic research, networking with peers, and surfacing innovative strategies.
- Breadth of interest or experience with diverse data-application domains (structured, unstructured, time-series, sensor, etc.).
- Experience with Git fundamentals (branching, merging, pull-requests, basic workflow conventions).
- Understanding of RESTful APIs and ability to integrate them into data pipelines.
- Basic familiarity with Docker (or comparable container technology).
Responsibilities
- Conducting experiments
- Building solutions
- Partnering with stakeholders and analysts to identify new opportunities utilizing large sets of structured and unstructured data
- Applying advanced technologies and scientific principles to uncover meaningful patterns in ambiguous problem spaces
- Modeling complex business challenges
- Delivering actionable insights
- Building production-grade solutions
- Identifying 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
- Discovering insights
- Providing actionable recommendations
- Guiding the team’s technical direction
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
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
