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 (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 & Tools
Experience 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 Environment
This 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.