Staff AI/ML Engineer

VTGManassas, VA
Hybrid

About The Position

VTG is seeking a highly experienced and innovative Staff AI/ML Engineer to lead the design, development, evaluation, and deployment of advanced artificial intelligence solutions in support of mission-critical and enterprise initiatives. This position is located in northern Virginia. The ideal candidate is both technically exceptional and customer-facing — capable of advising senior leadership, engaging directly with government and commercial stakeholders, and serving as a trusted authority on emerging AI technologies and best practices. This individual must have hands-on experience building and operationalizing AI systems and possess a strong understanding of modern AI governance, responsible AI principles, and evaluation methodologies.

Requirements

  • Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, or related technical field
  • 5+ years of experience in artificial intelligence, machine learning, software engineering, data engineering, or related technical disciplines
  • Statistical modeling and AI evaluation methodologies
  • Experience with AI testing, validation, benchmarking, and evaluation frameworks for both traditional ML and generative AI systems
  • Experience implementing practical MLOps pipelines and AI operationalization frameworks
  • Strong programming experience with: Python, Jupyter Notebooks or equivalent notebook environments
  • Experience with big data and distributed processing technologies such as: Apache Spark, Databricks (preferred)
  • Experience with one or more major cloud platforms: Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP)
  • Familiarity with: Containerization and orchestration technologies CI/CD pipelines for AI deployments
  • Strong communication and presentation skills with demonstrated customer-facing experience
  • Ability to translate complex technical concepts into actionable business and mission solutions
  • Active Secret security clearance required, or ability to obtain and maintain a Secret clearance.

Nice To Haves

  • Master’s degree or PhD
  • Experience supporting Federal Government, DoD, Intelligence Community, or highly regulated environments
  • Experience implementing secure AI architectures in classified or sensitive environments
  • Expertise in modern AI/ML architectures, including agentic AI systems, large language models (LLMs), autonomous workflows, AI evaluation frameworks, and production-grade machine learning operations (MLOps)
  • Design scalable MLOps and AIOps pipelines to support secure and repeatable deployment of AI capabilities in enterprise and cloud environments
  • Demonstrated experience architecting and deploying enterprise-scale AI/ML solutions in production environments
  • Hands-on experience building and operationalizing: Agentic AI systems LLM-powered applications; AI orchestration frameworks; Autonomous decision-support systems
  • Familiarity with AI security, adversarial AI, and zero trust principles
  • Experience with GPU infrastructure, model optimization, and scalable inference architectures
  • Familiarity with: Vector databases; AI orchestration frameworks (LangChain, Semantic Kernel, CrewAI, AutoGen, etc.)
  • Published research, conference presentations, patents, or contributions to the AI community preferred
  • Active participation in AI research communities, industry working groups, or open-source AI initiatives

Responsibilities

  • Architect, design, and implement advanced AI/ML solutions, including: Autonomous and semi-autonomous workflows, AI orchestration frameworks, Predictive analytics and traditional ML models
  • Lead the end-to-end AI lifecycle, including: Data ingestion and preparation, Model development and fine-tuning, AI testing and evaluation, Model deployment and monitoring, Operational sustainment and optimization
  • Develop and mature AI evaluation and testing methodologies, including: Traditional ML evaluation metrics, Red teaming and adversarial testing, Bias and fairness assessments, Performance and reliability testing, Human-in-the-loop evaluation strategies
  • Establish and implement AI governance frameworks, including: Responsible AI practices, Security and compliance controls, Model transparency and explainability, Risk management, Data governance standards
  • Collaborate across engineering, cybersecurity, cloud, data, and product teams to deliver integrated AI solutions
  • Serve as a senior technical advisor to customers, executives, and program leadership on AI strategy, architecture, modernization, and emerging capabilities
  • Lead technical discussions, architecture reviews, demonstrations, and customer briefings with confidence and authority
  • Stay current with emerging AI research, industry trends, open-source technologies, and commercial AI platforms; continuously assess applicability to organizational and customer needs
  • Mentor engineers, data scientists, and software developers on AI best practices, architectures, and implementation strategies
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