Role overview
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.
What we're looking for
- 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.