{"id":2109820,"url":"https://alion.io/job/lockheed-martin-ai-machine-learning-engineering-sr-3","title":"AI Machine Learning Engineering Sr","company":{"id":37086,"name":"Lockheed Martin","domain":"lockheedmartin.com","url":"https://alion.io/company/lockheedmartin","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":99,"open_postings":83,"ghost_share":0,"stale_share":0,"repost_share":0.048,"time_to_fill_p50_days":27,"computed_at":"2026-10-08T05:49:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Orlando, United States","Fort Worth, United States","Littleton, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":98100,"max":182100,"currency":"USD","period":"year","gross":null,"usd_annual":182100},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flyte","optional":false},{"name":"Machine Learning","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tokenomics","optional":false},{"name":"Apache Kafka","optional":true},{"name":"ChatGPT","optional":true},{"name":"CI/CD","optional":true},{"name":"Copilot","optional":true},{"name":"Docker","optional":true},{"name":"Grafana","optional":true},{"name":"GraphQL","optional":true},{"name":"Kubernetes","optional":true},{"name":"Power BI","optional":true},{"name":"Rest API","optional":true},{"name":"Spark","optional":true},{"name":"Streamlit","optional":true}],"status":"live","first_seen_at":"2026-10-08T13:14:55Z","employer_posted_date":"2026-10-08","last_verified_at":"2026-10-09T01:52:42Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Standard Job Description\nResponsible for developing, integrating, and deploying autonomy and artificial intelligence algorithms for mission systems, supporting the technology development life cycle from requirements generation through development, integration, and testing, as well as research in some organizations. Develops, integrates, and implements algorithms to enable perception, motion/mission planning, controls, etc. functionality in LM products and platforms; Translates requirements and applies requirements to development code, integrating autonomy, AI or machine learning algorithms to LM products and platforms; Determines software methods to best acquire and execute knowledge; Implements algorithms into software to train systems to recognize patterns and perform specific functions; Responsible for various phases of developing and maintaining autonomy software from requirements generation, software design and development to integration, testing, troubleshooting and debugging, and implementation; Review test outcomes, conducts troubleshooting, and works to debug issues; Develops human-machine interface scenarios, breaking missions into tasks; Documents interface requirements and implements human-machine interfaces.\nThe Lockheed Martin Artificial Intelligence Center (LAIC) seeks a curious and action-biased AI Adoption Analytics & Data Specialist with a strong background in data engineering, generative AI, and developer enablement. This role blends data pipeline engineering with user and executive storytelling to support enterprise-wide AI transformation. You’ll design and maintain the data infrastructure that powers AI adoption & tokenomics measurement to ensure these solutions deliver measurable impact for Lockheed Martin teams.\nData Pipeline Design & Development\nArchitect and implement end-to-end data pipelines that ingest, transform, and deliver data from diverse enterprise sources to support AI adoption programs and analytics.\nDesign ETL/ELT workflows using Python, SQL, Flyte, and/or similar orchestration tools to process structured and unstructured data at scale.\nBuild and maintain data models optimized for AI/ML datasets, adoption metrics, and executive visualizations.\nDevelop automated data quality checks, validation rules, and monitoring to ensure pipeline reliability and data integrity.\nAI Adoption Analytics & Measurement\nCreate data infrastructure supporting AI adoption KPIs.\nBuild pipelines that aggregate and normalize data from Generative AI and other internal AI platforms to provide unified adoption reporting.\nSynthesize adoption metrics, developer feedback, and market trends into executive-ready reports and decision packages.\nDevelop real-time and batch data feeds for leadership dashboards that track AI maturity across business areas and programs.\nData Integration, Governance & Security\nIntegrate data from multiple internal platforms, HR systems, learning management systems, and AI tools into cohesive, AI-ready datasets.\nDocument data lineage, maintain data dictionaries, and enforce governance standards across all pipeline outputs.\nCollaborate with cybersecurity and IT teams to ensure secure data transfer and storage within on-premises and classified environments.\nCommunity & Ecosystem Development\nServe as a bridge between developers, data teams, product teams, and leadership to ensure alignment on priorities and roadmap.\nContribute to the AI Factory ecosystem by developing reusable data components, integration patterns, and shared services.\nPartner with engineering leaders to identify tool and solution gaps, and influence product direction based on developer feedback and adoption data.\nProvide technical guidance to junior team members on data engineering best practices.\nBasic Qualifications\nBachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related STEM field.\n5+ years of professional experience in data engineering, data pipeline development, AI strategy, developer relations, or technical program management.\nProficiency in Python and SQL for data manipulation, transformation, and pipeline automation.\nHands-on experience with data orchestration tools (Flyte, AirByte, Apache Airflow, Prefect, Luigi, or equivalent).\nExperience with relational databases (PostgreSQL, MySQL, or similar).\nStrong technical understanding of generative AI, developer tools, and modern software development workflows.\nExcellent communication and storytelling skills, with the ability to engage both technical and executive audiences.\nDesired Skills\nExperience with data pipelines in defense, aerospace, or highly regulated industries.\nFamiliarity with AI/ML data preparation workflows, feature engineering, and training data management.\nExperience with streaming data platforms (Kafka, Spark Streaming, or equivalent).\nKnowledge of data visualization tools (Streamlit, React, Power BI, or Grafana) for dashboard integration.\nHands-on experience with AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, internal LLMs).\nProven ability to build and sustain technical communities.\nExposure to containerization (Docker, Kubernetes) and CI/CD for data pipeline deployment.\nExperience with API development (REST, GraphQL) for data service layers.\nFamiliarity with Lockheed Martin internal platforms (Navigator, Genesis, AI Factory).\nPay Information\nGeoZone Definition: GeoZones are geographic groupings created by Lockheed Martin to align compensation ranges with regional labor markets and cost-of-labor differences across the United States. Locations are assigned a Geo Zone based on the primary work location of the role.\nFull-time salary range (GEOZONE 1): $122600.00 - $227600.00 Includes metropolitan areas such as Sunnyvale CA; Pal Alto, CA; New York City metropolitan area; Newark, New Jersey; etc.\n\nFull-time salary range (GEOZONE 2): $110300.00 - $204900.00 Includes metropolitan areas such as Denver, CO; King of Prussia, PA; Stratford, CT; Moorestown, NJ; etc.\n\nFull-time salary range (GEOZONE 3): $98100.00 - $182100.00Includes metropolitan areas such as Dallas-Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.\n\nFull-time salary range (GEOZONE 4): $88300.00 - $163900.00Includes metropolitan areas such as Camden, AR; Lexington, KY; Lufkin, TX; etc. \n\nAt 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.\nThe salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only.\nLockheed 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.\nBenefits 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.\nAnnual 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.\nFor (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. 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