A/AI Machine Learning Engineering Sr

Standard Job Description

Responsible 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.

Join our team as a Senior Data Engineer building the data pipelines and semantic layer for our enterprise data platform. Our current focus is an AI-driven factory that turns business data needs into governed, tested data products on Databricks. You will also work on the team's other data and software projects, including CI/CD automation.

You will own pipeline capabilities end to end, within the standards set by the team's architects. You will decide whether AI-generated pipelines are correct, and review the work of early-career data engineers.

You will own work from design through production support. You must be comfortable with unclear requirements, unfamiliar enterprise data, changing priorities, and strict security constraints.

Responsibilities include:

• Own a pipeline capability end to end, such as incremental loads or data quality evidence.

• Build data pipelines on Databricks, and extend the reusable components that engineers and AI agents build pipelines from.

• Design and build incremental and historical loads, such as MERGE, change data capture, and SCD Type 2.

• Review AI-generated pipelines, mappings, joins, and incremental logic, and sign off on them within the team's standards.

• Write test data, independent expected results, and data quality rules, and add scenarios to the team's benchmark suites.

• Work directly with requesters, domain experts, and data owners to set grain, keys, business rules, and acceptance criteria for each product.

• Build semantic layer definitions, such as Unity Catalog metric views, from the data architect's designs.

• Map data products and source data to the enterprise ontology, following the data architect's design.

• Write data contracts and the quality evidence that shows each product can be trusted.

• Deploy pipelines as code through CI/CD, and support your releases in production, including freshness and quality monitoring.

• Review the work of early-career data engineers and help mentor them.

• Use AI coding assistants daily, and review what they generate before it ships.

• Document pipelines, tests, and decisions.

This is an individual contributor role. You will lead technical work in your area without formal personnel authority.

Basic Qualifications

• A bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related STEM field, with five years of relevant experience. A master's degree with three years of relevant experience can satisfy the education and experience requirement.

• Experience building and supporting production data pipelines, including deploying them as code through CI/CD.

• Strong SQL and data modeling, including grain, keys, deduplication, and layered (bronze, silver, gold) design.

• Experience with Python and Spark (PySpark) on a lakehouse or cloud data platform.

• Experience with incremental and historical loads, such as MERGE, change data capture, or SCD Type 2.

• Experience writing data quality rules and testing pipelines against independent expected results.

• Experience using AI coding assistants, such as Claude Code or similar tools, in daily development, including reviewing the code they generate.

• Strong communication skills, including working directly with data requesters and owners.

Desired Skills

• Experience with Databricks, including Unity Catalog, Delta Lake, and Lakeflow (Spark Declarative Pipelines).

• Experience with Databricks Jobs and Asset Bundles, or similar tools for deploying pipelines as code.

• Experience with semantic layers, such as Unity Catalog metric views, Databricks Genie, or dbt semantic models.

• Experience with data contracts, such as the Open Data Contract Standard (ODCS).

• Experience with ontologies or knowledge graphs, such as RDF, OWL, SKOS, SHACL, or SPARQL.

• Experience reviewing AI-generated code or evaluating LLM output against expected results.

• Experience with data governance, data catalogs, or data products.

• Experience with enterprise source data from SAP, MES, or PLM systems.

• Experience mentoring or reviewing the work of other engineers.

• Databricks certifications, such as Data Engineer Associate or Professional.

Pay Information

GeoZone 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.

• Full-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.

• Full-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.

• Full-time salary range (GEOZONE 3): $98100.00 - $182100.00

• Includes metropolitan areas such as Dallas–Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.

• Full-time salary range (GEOZONE 4): $88300.00 - $163900.00

• Includes metropolitan areas such as Camden, AR; Lexington, KY; Lufkin, TX; etc.

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.

Lockheed Martin is an equal opportunity employer. Qualified candidates will be considered without regard to legally protected characteristics.