Operations AI Engineer Senior - Level 3

Employer description

Standard Job Description
What You Will Be Doing
As the Operations AI Engineer Senior - Level 3 you will be responsible for leading exploratory research and analysis that identifies novel patterns in complex data, applying statistical methods to validate hypotheses, and delivering business‑focused insights.

Your responsibilities will include:

Conduct exploratory data analysis to uncover patterns and trends in large data sets.Develop and validate predictive models using advanced statistical, deep‑learning, and optimization techniques.Design and implement high‑performance computing solutions (GPU, distributed, cloud) to accelerate processing.Translate model insights into actionable recommendations with clear visualizations for stakeholders.Collaborate with cross‑functional teams to integrate analytics into business decision‑making. 

What’s In It For You
We are committed to supporting your work‑life balance and overall well‑being, offering flexible scheduling options. Learn more about Lockheed Martin’s comprehensive benefits package here. Do you want to be part of a company culture that empowers employees to think big, lead with a growth mindset, and make the impossible a reality? We provide the resources and give you the flexibility to enable inspiration and focus – if you have the passion and courage to pursue challenging work, work hard, and have fun doing what you love then we want to build a better tomorrow with you.

Who You Are
A collaborative professional with deep expertise in applied statistics, machine learning, and high‑performance computing. You thrive on turning complex data into actionable business value, enjoy mentoring teammates, and seek continuous growth in cutting‑edge AI research.

Further Information About This Opportunity

MUST BE A U.S. CITIZEN - This position is located at a facility that requires special access.The selected candidate must be able to obtain a secret clearance.This position is in Fort Worth, TX.  Discover Fort Worth 

Perform exploratory research and analysis to identify novel and meaningful patterns in data and uses statistical methods to reject or accept proposed hypotheses about relationships or latent predictive factors discovered through their work to provide business value. Uses a combination of tools, technologies, and numerical computing systems (i.e.: GPU processing, distributed computing, highly parallel coding, cloud computing, machine learning, visualization, system modelling and simulation) to achieve results. Areas of expertise should include several of the following: applied statistics, text mining, natural language processing, deep learning, optimization, and other similar fields. Work on datasets with applied statistics and machine learning algorithms; Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and discover opportunities in datasets to support decision-making; Develop predictive models and new algorithms to solve data / business problems; Understand the math and statistics behind the models and interpret, extrapolate, and prescribe from data to deliver actionable recommendations using effective visualizations

Basic Qualifications
Bachelor’s degree in Computer Science, Engineering, AI/ML or related fieldProficiency in Python and foundational machine learning concepts, with the ability to independently develop, train, and evaluate modelsExperience in developing, training, and deploying deep learning models using machine learning frameworks like TensorFlow and PyTorch.Demonstrated expertise in statistical modeling, hypothesis testing, and performance validation of AI modelsExperience with large dataset managementExperience with and maintaining CI/CD pipelinesAbility to translate complex operational requirements into scalable AI architecturesDesired Skills
Master’s degree in Computer Science, Engineering, AI/ML or related fieldFamiliarity with Large Language Models (LLMs) and/or Generative AI (GenAI)Familiarity with GenAI Coding AssistantsExperience with agentic AI frameworksExperience in API Development & Integrationknowledge of cloud platforms (AWS, Azure, GCP) and container orchestration (Docker,Kubernetes).Experience with data‑governance frameworks, metadata management, and data catalog tools.Experience with aircraft manufacturing processesStrong organization and communication skillsPay Information

Full-Time Salary Range: $98100.00 - $182100.00

At Lockheed Martin, we know mission success starts with taking care of our people. Our Total Rewards program is designed to attract top talent, support your well-being, and help you grow—both professionally and personally.

The salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only. Lockheed Martin considers factors such as (but not limited to) scope and responsibilities of the position, candidate’s work experience, education/ training, key skills as well as market(work location) and business considerations when extending an offer.  

Benefits offered: Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, and Long-Term Disability.

Annual short-term and/or long-term incentive compensation programs may be offered depending on the position. Payments under these annual programs are not guaranteed and can vary from year to year and are tied to a range of performance metrics.For (Washington state applicants only) Non-represented full-time employees: accrue at least 10 hours per month of Paid Time Off (PTO) to be used for incidental absences and other reasons; receive at least 90 hours for holidays. Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of sick leave annually; receive at least 96 hours for holidays. PTO, Vacation, sick leave, and holiday hours are prorated based on start date during the calendar year.