Job description

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.

Requirements

Must-haves

Standard Job Description
Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or related technical field
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

Nice-to-haves

Master's degree or PhD in Machine Learning, Artificial Intelligence, or related field preferred
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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpythonsqlawsazuregcpci/cddockerkubernetes

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Paid Time Off

Parental Leave