Applied AI ML Engineer at SAIC

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Full Time

Start Date

Immediate

Expiry Date

18 Feb, 26

Salary

0.0

Posted On

20 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI/ML Solutions, Large Language Models, Computer Vision, Advanced Analytics, Predictive Analytics, Anomaly Detection, Decision Support Systems, Data Pipelines, Secure Coding Practices, Cloud Environments, DoD Compliance, Experimental Methodologies, Cross-Functional Collaboration, Performance Monitoring, Open-Source Contributions, RAG Systems Optimization

Industry

Defense and Space Manufacturing

Description

SAIC is seeking an Applied AI/ML Engineer - DoD Systems Integration who will play a critical role in designing, developing, and deploying advanced AI/ML solutions to support mission-critical systems for the Department of Defense (DoD). The Applied AI/ML Engineer will work on cutting-edge technologies, including large language models (LLMs), computer vision, and advanced analytics, to solve complex challenges in defense and national security. Collaborating with cross-functional teams, the candidate will ensure that AI/ML solutions are robust, secure, and aligned with DoD requirements and compliance standards. The Applied AI/ML Engineer will be Responsible for but not limited to the following: Design, develop, and deploy AI/ML models and pipelines to address DoD-specific challenges, such as predictive analytics, anomaly detection, and decision support systems. Build and optimize LLM-based systems for tasks like natural language understanding, document summarization, and knowledge extraction. Develop and maintain data pipelines, including preprocessing, feature engineering, and integration with DoD systems. Implement and evaluate AI/ML models using rigorous experimental methodologies, including proper train/validation/test protocols, statistical significance testing, and ablation studies. Collaborate with system architects, engineers, and program managers to integrate AI/ML solutions into existing DoD systems and workflows. Ensure compliance with DoD security and data handling standards, including adherence to the DoD Enterprise DevSecOps initiative. Monitor and evaluate the performance of deployed models, iterating to improve accuracy, efficiency, and reliability. Stay current with advancements in AI/ML research and apply state-of-the-art techniques to DoD use cases. Document technical designs, experimental results, and system performance for both technical and non-technical stakeholders Required Education: Bachelor's degree and five (5) years’ experience; additional four (4) years’ experience can be considered in lieu of degree. Required Clearance: Must possess an active Secret security clearance with the ability to maintain; US Citizenship required. Required Skills: Experience working with DoD systems, including knowledge of compliance frameworks like RMF (Risk Management Framework) and the DoD Enterprise DevSecOps initiative. Hands-on experience with RLHF pipelines, reward modeling, or behavioral policy tuning in LLMs. Familiarity with secure coding practices and deployment of AI/ML models in cloud environments (e.g., AWS GovCloud, Azure Government). Contributions to open-source projects or publications in applied AI/ML. Desired Skills or Required Certifications: Experience optimizing RAG systems and tuning retrieval performance using custom embeddings or search strategies. Knowledge of integrating AI/ML systems into mission-critical workflows, such as command and control (C2) systems or ISR (Intelligence, Surveillance, and Reconnaissance) platforms.

Responsibilities

The Applied AI/ML Engineer will design, develop, and deploy AI/ML models and pipelines to address DoD-specific challenges. They will collaborate with cross-functional teams to integrate AI/ML solutions into existing systems while ensuring compliance with DoD standards.