AI/ML Engineer (TS Clearance)

Assured Consulting Solutions

• $120K — $145K *
Aerospace & Defense
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree or higher in a related STEM field, or equivalent experience
  • Hands-on experience in machine learning engineering and model development with production deployment
  • Strong software engineering skills in Python for various ML workflows
  • Experience with machine learning model evaluation in production environments
  • Demonstrated ability to implement and operate LLM-enabled applications
  • Experience with MLOps infrastructure including experiment tracking and deployment practices
  • Strong communication skills for conveying complex technical details to diverse audiences

Responsibilities

  • Develop and automate model training pipelines using custom code or tools
  • Create AI/ML solutions tailored to mission-specific needs
  • Design and optimize machine learning models for critical use cases
  • Research innovative modeling approaches to enhance mission capabilities
  • Collaborate with stakeholders to translate needs into technical designs
  • Build MLOps pipelines for reliable model deployment and tracking
  • Integrate AI/ML services into applications

Benefits

  • Flexible hybrid work schedule (3 days onsite, 2 days remote)
  • Access to cutting-edge tools and technologies in AI/ML
  • Participation in innovative projects within national security missions
  • Opportunities for continuous learning and professional development
  • Collaborative work environment supporting cross-functional teams
Full Job Description
Job Status: Funded and Active

Location: Reston, VA or Bolling AFB, DC (hybrid onsite [generally 3 days on site and 2 days off site] once fully cleared)

Clearance Required: Must be a U.S. Citizen and possess a current and active Top Secret clearance. Must be eligible for a clearance upgrade to SCI and able to pass a Counterintelligence (CI) Polygraph. Having a current TS/SCI and/or CI Polygraph is a plus. Once TS/SCI is obtained it must be maintained for continued employment.

Responsibilities include, but are not limited to:
  • Develop and automate fine-tuning and model training pipelines using available tools or custom code.
  • Develop innovative AI/ML and LLM-enabled solutions to address specific mission challenges and operational needs.
  • Design, implement, and optimize machine learning models for new mission-critical use cases and features.
  • Conduct research on novel modeling approaches, architectures, and techniques to maximize mission capability and competitive advantage.
  • Work with mission leads and stakeholders to translate operational needs into technical AI/ML designs and implementation plans.
  • Build and maintain MLOps and model deployment pipelines for experiment tracking, model versioning, and reliable production releases.
  • Define and track model performance metrics aligned to mission success criteria and use evaluation findings to drive improvements.
  • Integrate AI/ML model services into application workflows through APIs and production-ready interfaces.
  • Partner with Data Integration Engineers to utilize curated training datasets, test corpora, and evaluation frameworks.
  • Collaborate with Senior Software Engineers to operationalize AI/ML capabilities within secure, mission-focused application environments.
  • Implement guardrails, monitoring, and fallback strategies for responsible and reliable AI/ML-enabled operations.
  • Analyze model behavior, identify performance gaps, and innovate on approaches to improve quality, reliability, and mission impact.
  • Document model designs, assumptions, training methodologies, evaluation results, and operational guidance for sustainability and knowledge transfer.
  • Support production troubleshooting and performance optimization for mission-critical model-serving workloads.
  • Contribute to technical standards and best practices for responsible, secure AI/ML engineering in mission environments.

Required Qualifications:
  • Bachelor's degree or higher in a related STEM field, or equivalent experience
  • Hands-on experience in machine learning engineering, applied AI, or model development with demonstrated model deployment to production.
  • Strong software engineering skills in Python for model development, training, inference, and experimentation workflows.
  • Experience developing and evaluating machine learning models (supervised, unsupervised, or reinforcement learning) in production or mission-focused contexts.
  • Demonstrated experience implementing and operationalizing LLM-enabled applications or features, including prompting strategies, retrieval approaches, and integration patterns.
  • Experience building and maintaining MLOps infrastructure, including experiment tracking, model versioning, reproducibility, and continuous deployment practices.
  • Experience defining model performance metrics, conducting model evaluation, and using evaluation results to drive improvements.
  • Experience deploying and operating model services in containerized environments (for example OpenShift or Kubernetes).
  • Demonstrated case studies or examples of innovative use of AI/ML to solve domain-specific or mission-critical problems.
  • Demonstrated ability to communicate technical complexity, model assumptions, and performance limitations clearly to both technical and non-technical stakeholders.
  • Understanding of secure development, secure AI practices, and deployment governance in controlled or classified environments.

Desired Qualifications:
  • Experience supporting DIA or comparable intelligence community mission environments and problem sets.
  • Experience with AWS and C2E cloud environments for AI/ML workload and model serving.
  • Experience with advanced model-serving frameworks, orchestration, or inference optimization.
  • Familiarity with ontology-driven data modeling or semantic technologies (for example RDF, OWL, or knowledge graphs) for structured reasoning.
  • Experience with retrieval-augmented generation (RAG), vector search, knowledge-grounded LLM approaches, or semantic search.
  • Experience with multi-model or ensemble approaches for improved performance or robustness.
  • Familiarity with DevSecOps practices and model release governance in secure environments.
  • Experience evaluating and improving reliability, observability, and performance monitoring for mission-critical AI systems.

Education Qualifications:
  • Bachelor's degree or higher in a related STEM field, or equivalent experience

Years of Experience:
  • 5+ years w/ Bachelor's Degree, Master's Degree, or PhD

Essential Job Functions:

The Americans with Disabilities Act (ADA) requires employers to identify the essential functions of a position to determine whether an individual is qualified. Essential job functions are the fundamental duties of the position that must be performed, with or without reasonable accommodation.
The essential functions of this position include:
  • Ability to work onsite in a Sensitive Compartmented Information Facility (SCIF) environment, as required
  • Ability to collaborate effectively with government customers, technical teams, and cross-functional partners
  • Ability to communicate clearly and effectively, both verbally and in writing
  • Ability to operate standard office equipment and remain in a stationary position for extended periods
  • Ability to analyze complex system requirements and develop technical recommendations
  • Ability to contribute to systems engineering, integration, and evaluation efforts across the lifecycle
  • Ability to support technical planning, risk identification, and system improvement initiatives
  • Ability to work independently while contributing to team objectives in a fast-paced environment
  • Ability to manage multiple priorities and deliver high-quality work under deadlines

Position Type: Full-Time

Shift: Day

Export Control: For all positions requiring access to technology/software source code that is subject to export control laws, employment with the company is contingent on either verifying U.S.-person status or obtaining any necessary license. The applicant will be required to answer certain questions for export control purposes, and that information will be reviewed by compliance personnel to ensure compliance with federal law. ACS may choose not to apply for a license for such individuals whose access to export-controlled technology or software source code may require authorization and may decline to proceed with an applicant on that basis alone.

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