Machine Learning Engineer Job at Caci, San Antonio, TX

  • Caci
  • San Antonio, TX

Job Description

Job Title: Machine Learning Engineer

Job Category: Science

Time Type: Full time

Minimum Clearance Required to Start: TS/SCI

Employee Type: Regular

Percentage of Travel Required: Up to 10%

Type of Travel: Local

* * *

The Opportunity:

The 35th Intelligence Squadron seeks a motivated AI/ML Engineer to develop and deploy complex Artificial Intelligence systems defending the Department of Defense Air Force Information Network (AFIN). The role requires anomaly detection algorithms for identifying and isolating malicious threats using supervised and unsupervised learning, Graph Neural Networks, and Deep Learning models.

You will drive our cyber threat intelligence and detection mission by providing expert leadership and mentorship in advanced AI/ML solutions, augmenting cyber threat analysts triaging 1TB+ of boundary device logs daily to produce defensible intelligence reports with real mission consequences. You will provide technical direction for the design, implementation, testing, deployment, and operation of the 35 IS's cyber threat detection methods and enabling systems.

Responsibilities:

  • Design & Deplo y: Architect, build, and deploy high-performance ML models with 1TB+ daily ingestion across heterogeneous data sources into production, ensuring scalability, reliability, and low latency.

  • Drive the ML Lifecycle : Lead data preparation, model development, evaluation, monitoring, drift detection, and continuous retraining within mission-aligned constraints.

  • Model Innovation: Develop and implement state-of-the-art algorithms, specifically a hybrid GNN and BiLSTM architecture operating on a continuously updated heterogeneous network graph.

  • Optimize: Improve model performance through feature engineering, hyperparameter tuning, and advanced experimentation.

  • Mentorship : Mentor junior software developers and provide technical guidance and expertise.

  • Logistics : Ensure appropriate documentation for all delivered analytics. Build explainability into the product from the beginning to support defensible intelligence reports. Ensure analyst trust is a design requirement, not an afterthought.

  • Innovation : Guide analytic approaches where information is incomplete or no precedent exists. Apply that experience to real constraints: classification boundaries, data that cannot be shared with vendors, upstream pipeline failures, and out of order log delivery.

  Qualifications:

Required:

  • Clearance: Active TS/SCI security clearance.

  • Certification: DOD Directive 8140.01 (Security+ or equivalent must be obtained within 6 months of hire).

  • Experience: 5+ years in Machine Learning focused on deploying models into production.

  • Education: Master's in Data Science, AI, or related quantitative field preferred.

  • Technical Skills: Deep knowledge of ML frameworks such as PyTorch or TensorFlow.

  • Programming: Strong Python. ML libraries including Spark MLlib, Scikit-learn, XGBoost, Keras, Hugging Face, PyTorch Geometric, MLflow. Explainability tools such as SHAP, GNNExplainer, or attention-based interpretation methods.

  • Data: Extensive experience incorporating data from multiple sources, labeling data for training, and identifying hidden patterns.

  • Visualization: Matplotlib, Grafana, or Kibana. Communication: Ability to communicate complex problems and solutions to non-technical leadership.

Desired:

  • 2+ years developing analytic solutions at scale over multiple PB of data.

  • Experience with:

    • Elasticsearch (ELK stack) and Lucene.

    • Docker/Kubernetes and containerized products.

    • CI/CD pipelines and Git.

    • Data pipelines - Pandas, NumPy, NiFi, Kafka, or similar.

    • Confluence, Jira, and collaborative platform experience.

    • Software engineering best practices across the full development lifecycle.

    • Familiarity with network defense, cybersecurity principles, and threat hunting.

    • Familiarity with data collection, storage, and monitoring.

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What You Can Expect:

 A culture of integrity.

At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation.

An environment of trust.

CACI values the unique contributions that every employee brings to our company and our customers - every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.

A focus on continuous growth.

Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy.

Pay Range :

There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.

The proposed salary range for this position is:

$93,500 - $196,500

CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.

Job Tags

Full time, Contract work, Work experience placement, Local area, Flexible hours

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