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AI​/ML Engineer

Job in Chantilly, Fairfax County, Virginia, 22021, USA
Listing for: Vosper Thornycroft Group
Full Time position
Listed on 2026-07-04
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 130000 - 160000 USD Yearly USD 130000.00 160000.00 YEAR
Job Description & How to Apply Below
Position: Staff AI/ML Engineer

Overview

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 system and possess a strong understanding of modern AI governance, responsible AI principles, and evaluation methodologies.

What will you do?

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
Do you have what it takes?

Required Qualifications
  • 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
Preferred Qualifications
  • 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 (Lang Chain, Semantic Kernel, CrewAI, Auto Gen, etc.)
  • Serve as a senior technical advisor to customers, executives, and program leadership on AI strategy, architecture,…
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