The Role
Develops, integrates, tests, and deploys AI and machine learning algorithms for data engineering platforms. Builds intelligent orchestration, data quality validation, metadata discovery, anomaly detection, predictive operations, and automation capabilities. Integrates ML into ETL/ELT workflows and cloud data infrastructure, troubleshoots production systems, and creates interfaces enabling data teams to use AI tools. Requires expert Python, production ML, MLOps, cloud, data engineering, and leadership expertise.
Summary Generated by Built In
Standard Job Description
Responsible for developing, integrating, and deploying artificial intelligence and automation algorithms for data engineering systems, supporting the technology development life cycle from requirements generation through development, integration, and testing. Develops, integrates, and implements algorithms to enable intelligent data pipeline orchestration, automated data quality validation, metadata discovery, anomaly detection, and predictive data operations functionality within data engineering platforms and tooling. Translates requirements from data engineering teams and applies them to development code, integrating AI, machine learning, and automation algorithms into data platforms, ETL/ELT workflows, and data infrastructure. Determines optimal methods to acquire, process, and operationalize knowledge from data systems; implements algorithms to train systems to recognize data patterns, predict pipeline failures, optimize resource allocation, and automate routine data operations tasks. Responsible for various phases of developing and maintaining AI/automation software from requirements generation, software design and development through integration, testing, troubleshooting, debugging, and implementation. Reviews test outcomes, conducts troubleshooting, and debugs issues in production data systems. Develops human-machine interface scenarios for data engineers and analysts, breaking complex data workflows into automated tasks. Documents interface requirements and implements intuitive interfaces that enable data teams to leverage AI capabilities without deep ML expertise.
Basic Qualifications
- Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or related technical field
- Master's degree or PhD in Machine Learning, Artificial Intelligence, or related field preferred
- 10+ years professional experience, 5+ years in production ML
- Expert Python, deep learning frameworks (TensorFlow/PyTorch)
- ML fundamentals, cloud platforms, MLOps experience
- Leadership and communication skills
Desired Skills
- Programming: Expert-level proficiency in Python; strong SQL skills; experience with ML libraries (scikit-learn, pandas, NumPy, SciPy)
- Machine Learning Frameworks: Experience with TensorFlow, PyTorch, or JAX for deep learning; scikit-learn for traditional ML
- ML Fundamentals: Deep understanding of machine learning algorithms (especially anomaly detection, time series, NLP), statistical modeling, and optimization techniques
- Data Engineering Platforms: Hands-on experience with modern data orchestration tools (Airflow, Prefect, Dagster) and data transformation frameworks (dbt)
- Big Data Technologies: Production experience with Spark, distributed computing, and processing large-scale datasets
- Data Warehouses: Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, or Databricks)
- SQL Mastery: Advanced SQL skills including query optimization, window functions, CTEs, and performance tuning
- Cloud Platforms: Production experience with AWS, Azure, or GCP (both ML services and data platform services like S3, GCS, Azure Data Lake)
- Version Control & CI/CD: Proficiency with Git, GitHub/GitLab, and CI/CD pipelines for both ML models and data pipelines
- MLOps: Experience with model deployment, containerization (Docker), orchestration (Kubernetes), and integrating ML into data platforms
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): $150800.00 - $280000.00
- 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): $135700.00 - $251900.00
- Includes metropolitan areas such as Denver, CO; King of Prussia, PA; Stratford, CT; Moorestown, NJ; etc.
- Full-time salary range (GEOZONE 3): $120600.00 - $224000.00
- Includes metropolitan areas such as Dallas–Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.
- Full-time salary range (GEOZONE 4): $108600.00 - $201600.00
- 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.
Skills Required
- Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related technical field
- 10+ years of professional experience
- 5+ years of production machine learning experience
- Expert proficiency in Python
- Experience with deep learning frameworks such as TensorFlow or PyTorch
- Knowledge of machine learning fundamentals
- Cloud platform experience
- MLOps experience
- Leadership and communication skills
- Master's degree or PhD in Machine Learning, Artificial Intelligence, or a related field
- Strong SQL skills
- Experience with scikit-learn, pandas, NumPy, and SciPy
- Experience with Airflow, Prefect, Dagster, or dbt
- Production experience with Apache Spark and distributed computing
- Experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Databricks
- Advanced SQL including query optimization, window functions, CTEs, and performance tuning
- Production experience with AWS, Azure, or GCP and their data platform services
- Proficiency with Git, GitHub or GitLab, and CI/CD pipelines
- Experience with model deployment, Docker, Kubernetes, and ML integration into data platforms
Lockheed Martin Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lockheed Martin and has not been reviewed or approved by Lockheed Martin.
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Retirement Support — Retirement benefits are described as a standout element, with a strong 401(k) program and options like an employee stock purchase plan. Feedback suggests these features meaningfully enhance total compensation and long‑term financial security.
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Healthcare Strength — Healthcare coverage is portrayed as comprehensive from day one, with multiple plan options, mental health resources, and virtual care. Wellness supports such as on‑site services and preventive programs are also highlighted.
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Flexible Benefits — Work arrangements often include compressed schedules and telework, contributing to a favorable work‑life balance. Feedback suggests this flexibility is a key reason many view the overall package positively.
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The Company
What We Do
Customer Focus, Innovation and Purpose are Built Into Everything We Do. Lockheed Martin. Your Mission is Ours ™. Headquartered in Bethesda, Maryland, Lockheed Martin is a global security and aerospace company principally engaged in the research, design, development, manufacture, integration and sustainment of advanced technology systems, products and services.
