Machine Learning Engineer Principal

Job ID: 2612072

Location: San Diego, CA, US

Date Posted: 2026-04-30

Category: Engineering and Sciences

Subcategory: Machine Learning Engineer

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: None

Clearance Level Must Be Able to Obtain: Secret

Potential for Remote Work: ORA_HYBRID

Description

SAIC is seeking an AI/Machine Learning Engineer to support the Enterprise Center of Excellence (ECOE) in developing scalable, data-driven solutions for mission-critical aerospace and defense systems.

This role focuses on building applied machine learning capabilities on top of structured, governed data systems, enabling predictive analytics, anomaly detection, and decision support at the aircraft and system level.

The position bridges data engineering, analytics, and machine learning, supporting the transition from file-based data processing to enterprise data warehouse-driven intelligence.

This is a Hybrid/Remote role with preference to be residing in San Diego, CA

JOB DUTIES:

Data Pipeline & ML Integration

• Develop and maintain end-to-end data pipelines (API ingestion, transformation, and loading into structured data stores)
• Integrate machine learning models into production data workflows
• Work with cloud-based data platforms (AWS, S3, RDS/PostgreSQL)
  
  

Machine Learning & Analytics

• Develop and evaluate machine learning models for prediction, classification, and anomaly detection.
• Apply statistical analysis and NLP techniques to structured and semi-structured datasets
• Support feature engineering aligned with enterprise data models
  
  

Data Quality & Validation

• Ensure data integrity, traceability, and validation across pipelines and models
• Automate data validation and testing processes using Python and SQL
• Support governed data frameworks and reproducible analytics
  
  

Cloud & Big Data Technologies

• Work with AWS services (S3, EC2, Athena) and/or Google Cloud (BigQuery)
• Utilize distributed data processing tools (e.g., Spark) where applicable
• Support scalable data architectures for analytics and ML workloads
  
  

Stakeholder Engagement

• Collaborate with engineers, data scientists, and domain experts
• Present analytical findings and model outputs to technical and non-technical stakeholders
• Support customer-facing discussions and solution development
  
  

Qualifications

REQUIREMENTS:

• Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience; PhD or JD and four (4) years or more experience.
• Must be able to obtain a Secret Clearance after start
• Experience integrating and analyzing data from multiple sensor modalities and enterprise sources (e.g., maintenance, logistics, supply) to support readiness and maintenance analytics.
• Proficiency working in a Linux environment, including scripting, debugging, and system-level operations to support deployment and automation.
• Experience developing scalable data pipelines and orchestrating workflows (e.g., Airflow, NiFi, or similar tools).
• 3-7 years of experience in data engineering, analytics engineering, or applied ML
• Strong proficiency in:
• Python
• SQL
• Data pipeline development (API ingestion, ETL/ELT)
• Experience with cloud platforms (AWS or Google Cloud Platform)
• Experience working with structured data systems and relational databases
• Understanding of machine learning fundamentals and model evaluation
  
  

DESIRED SKILLS:

• Master's degree in Data Science or related field
• Experience with:
• Natural Language Processing (NLP)
• Spark or distributed data processing
• BigQuery or Snowflake
• Background in:
• Data validation, quality engineering, or regulated environments
• Experience presenting to stakeholders or customers
• Exposure to predictive modeling or forecasting use cases
• Strong data engineering mindset (pipelines, structure, automation)
• Ability to operationalize ML models-not just prototype
• Understanding of data governance and reproducibility
• Experience working in cross-functional engineering teams
• Strong communication and stakeholder engagement skills
  
  

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

SAIC is a premier technology integrator providing full life cycle services and solutions in the technical, engineering, intelligence, and enterprise information technology markets. SAIC is Redefining Ingenuity through its deep customer and domain knowledge to enable the delivery of systems engineering and integration offerings for large, complex projects. SAIC's approximately 15,000 employees are driven by integrity and mission focus to serve customers in the U.S. federal government. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $4.5 billion. For more information, visit saic.com. For information on the benefits SAIC offers, see .