Staff AI/ML Engineer
Actively Hiring
Full-time Posted 28 days ago
Role 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.
Responsibilities
- check_circle Autonomous and semi-autonomous workflows
- check_circle AI orchestration frameworks
- check_circle Predictive analytics and traditional ML models
- check_circle Data ingestion and preparation
- check_circle Model development and fine-tuning
- check_circle AI testing and evaluation
- check_circle Model deployment and monitoring
- check_circle Operational sustainment and optimization
- check_circle Traditional ML evaluation metrics
- check_circle Red teaming and adversarial testing
- check_circle Bias and fairness assessments
- check_circle Performance and reliability testing
- check_circle Human-in-the-loop evaluation strategies
- check_circle Responsible AI practices
- check_circle Security and compliance controls
- check_circle Model transparency and explainability
- check_circle Risk management
- check_circle Data governance standards
- check_circle Collaborate across engineering, cybersecurity, cloud, data, and product teams to deliver integrated AI solutions
Basic 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
- Active Secret security clearance required, or ability to obtain and maintain a Secret clearance.
- 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
- 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
Tags & Focus Areas
Fulltime Ai Ai Engineer Machine Learning Robotics
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