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AI ML Engineer

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Hybrid

AI ML Engineer

The Brite Group Incorporated

AI ML Engineer

Skills

Google Cloud PlatformReactPythonData ScienceMicroservicesCybersecurityData AnalysisMachine LearningAIAWS

24 days ago

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Important information


Contract type:

Permanent, Temporary

Salary:

$100,000 – $130,000 / year

Location:

Reston, VA, USA

Work mode:

Hybrid

Published on:

1 October 2026

What they need


AI/ML Engineer

Full-Time Salaried Role

Hybrid Role - 2 days in office, on Tuesdays and Thursdays in Reston, VA

U.S. Citizenship is required. Candidate must be eligible to obtain and maintain a Federal Government security clearance.

Ability to travel up to 50% of the time.

Description

Lead or contribute to cross-functional teams to develop and operationalize AI solutions that help solve our most challenging problems. - Apply modern engineering techniques to design, develop, deploy and maintain end-to-end AI workflows spanning model training, inference and performance monitoring. - Adapt and integrate diverse AI model architectures, including computer vision systems, natural language processors, audio processors, large language models (LLMs) and multi-modal frameworks to address complex mission-critical challenges. - Monitor and maintain AI products through systematic identification of performance degradation and computational inefficiency and address these challenges through regular fine-tuning to ensure continued alignment with evolving mission needs and organizational goals. - Maintain knowledge of current AI research and adapt emerging techniques to intelligence applications. - Test and evaluate AI solutions against mission requirements and produce actionable recommendations.

Job responsibilities

  • Design, develop, train, test, deploy, and maintain AI and machine learning models for enterprise-scale and Government applications.
  • Develop and operationalize production of AI/ML solutions, ensuring models and supporting systems are reliable, scalable, maintainable, and appropriate for VA mission requirements.
  • Collect, clean, transform, analyze, and prepare structured and unstructured data for AI/ML model development, training, testing, and evaluation.
  • Evaluate potential AI technologies, models, tools, frameworks, and architectures and recommend solutions appropriate for complex Federal Government and cybersecurity use cases.
  • Apply AI and machine learning techniques to solve real-world business, cybersecurity, engineering, analytics, and operational problems across a large enterprise environment.
  • Develop and support Generative AI and Large Language Model (LLM) solutions, including model configuration, system prompts, classifiers, fine-tuning, content moderation, safety filters, and other model controls.
  • Evaluate AI-generated outputs for accuracy, factuality, grounding, reliability, bias, helpfulness, honesty, and overall model performance before outputs are incorporated into VA efforts.
  • Design and execute AI/ML model evaluation and validation methodologies, including benchmark testing and comparative evaluation of model outputs.
  • Perform and support AI red-team testing to identify weaknesses, unintended model behaviors, bias, security vulnerabilities, and other risks associated with AI-generated outputs.
  • Implement mechanisms and controls to improve the factuality and grounding of AI/LLM outputs, including system-level instructions, source attribution, content controls, and appropriate response behavior when information is incomplete, contradictory, or uncertain.
  • Produce technical documentation, analysis, recommendations, briefings, and other materials that clearly communicate AI architecture, model performance, risks, controls, and recommended courses of action to both technical and non-technical stakeholders.
  • Deliver Government-owned AI-related technical artifacts developed under the program, including applicable models, model weights, algorithms, configurations, documentation, data models, source code, and supporting technical components.
  • Other responsibilities as assigned

Minimum qualifications

  • Minimum of 5 years of experience in relevant fields including IT security, data science, or software engineering, design, development, or deployment of AI or machine learning systems in enterprise or Government environments
  • Experience working on data science, machine learning, or AI projects, either through internships, research projects, or professional roles.
  • Experience building, training, and deploying machine learning models and AI systems in a production environment.
  • Experience collaborating with cross-functional teams, including data scientists, software developers, and domain experts.
  • Experience in data collection, cleaning, and analysis techniques to prepare datasets for AI modeling.
  • Experience applying AI solutions to real-world problems in various enterprises and domains such as large corporations and Government agencies similar in size/scope to GSA, IRS, DoD or VA
  • Bachelor's degree in engineering, Computer Science, a related field, or equivalent practical experience.
  • 5 years of experience with software development using Python or similar coding languages.
  • Experience architecting AI systems on cloud platforms (e.g., AWS, Google Cloud Platform).

Preferred qualifications

  • Master’s or PhD in AI, Computer Science, or related technical field.
  • Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
  • Experience debugging Agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
  • Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
  • Track record of troubleshooting live, high-traffic systems during critical windows.

Pay: $100,000.00 - $130,000.00 per year

Benefits:

  • 401(k)
  • Dental insurance
  • Flexible schedule
  • Health insurance
  • Paid time off
  • Vision insurance

Work Location: Hybrid remote in Reston, VA 20190

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