Senior AI/ML Engineer — Data Pipelines & LLMs (TS/SCI)

CACI; King of Prussia (PA); On-site; USD 82,000 - 172,000; Full time

Job summary

CACI is seeking a Senior AI/ML Engineer to advance AI/ML algorithms across LLM, NLP, and time-series analytics. You will join a multidisciplinary team building ETL pipelines to support AI/ML solutions addressing diverse customer challenges.

Required are a BS in data science/AI/ML/CS, 5+ years in data engineering/science or ML engineering, and active TS/SCI clearance. Expect collaboration across teams, scalable data systems, and agile development in a dynamic environment.

Qualifications

• B.S. in Data Science, AI/ML, Computer Science, or related field.
• 5+ years of experience in data engineering/science, ML engineering, or software development.
• Experience building data pipelines and normalizing data with canonical Python packages (e.g. NumPy, Pandas, Polars).
• Experience collaborating in a team using version control (Git).
• Active TS/SCI U.S. Government Security Clearance.

Responsibilities

• Assemble large, complex data sets to support AI/ML model implementation.
• Build infrastructure for ETL data extraction, transformation and loading from diverse sources.
• Curate and maintain data to support metrics and evaluation.
• Implement AI/ML algorithms and drive improvements across pipelines.
• Identify and implement internal process improvements for scalability and automation.
• Apply Agile software development methodologies.

Skills

AI/ML

Data Science

Software Development

Python

Education

B.S. in Data Science / AI/ML / CS

Tools

NumPy / Pandas / Polars

Git

Docker

Kubernetes

Job description

CACI is seeking a Senior AI/ML Engineer to advance AI/ML algorithms across LLM, NLP, and time-series analytics. You will join a multidisciplinary team building ETL pipelines to support AI/ML solutions addressing diverse customer challenges.

Required are a BS in data science/AI/ML/CS, 5+ years in data engineering/science or ML engineering, and active TS/SCI clearance. Expect collaboration across teams, scalable data systems, and agile development in a dynamic environment.