OverviewVTG 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 (Google Cloud Platform)
- 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 (LangChain, Semantic Kernel, CrewAI, AutoGen, etc.)
- 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
- 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
- Mentor engineers, data scientists, and software developers on AI best practices, architectures, and implementation strategies
Clearance Requirement- Active Secret security clearance required, or ability to obtain and maintain a Secret clearance.
Desired Characteristics- Strategic thinker with strong technical depth and hands-on engineering capability
- Passion for continuous learning and staying ahead of rapidly evolving AI technologies
- Comfortable operating in ambiguous and fast-paced technical environments
- Strong leadership, collaboration, and mentoring abilities
- Customer-focused with executive presence and consultative communication skills
Technologies & ToolsExperience with several of the following is desired:
- Python
- Jupyter Notebook
- Apache Spark
- Databricks
- TensorFlow
- PyTorch
- Hugging Face
- LangChain
- Semantic Kernel
- CrewAI
- AutoGen
- Kubernetes
- Docker
- Azure AI Services
- AWS SageMaker
- Google Vertex AI
- Vector databases
- MLflow
- GitLab/GitHub CI/CD pipelines
Work EnvironmentThis role may support hybrid, on-site, or customer-location work environments depending on program requirements. Occasional travel may be required for customer engagement, technical workshops, or industry events.
Never miss an opportunity! Create an alert based on the job you applied for.
