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.

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

Qualifications:

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.