Staff Data Scientist

OverviewVTG is seeking a highly experienced and innovative Staff II/Staff III 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 workflowsAI orchestration frameworksPredictive analytics and traditional ML modelsLead the end-to-end AI lifecycle, including:Data ingestion and preparationModel development and fine-tuningAI testing and evaluationModel deployment and monitoringOperational sustainment and optimizationDevelop andmature AI evaluation and testing methodologies, including:Traditional ML evaluation metricsRed teaming and adversarial testingBias and fairness assessmentsPerformance and reliability testingHuman-in-the-loop evaluation strategiesEstablish and implement AI governance frameworks, including:Responsible AI practicesSecurity and compliance controlsModel transparency and explainabilityRisk managementData governance standardsCollaborate across engineering, cybersecurity, cloud, data, and product teams to deliver integrated AI solutionsDo you have what it takes?Required Qualifications:Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, or related technical field5+ years of experience in artificial intelligence, machine learning, software engineering, data engineering, or related technical disciplinesStatistical modeling and AI evaluation methodologiesExperience with AI testing, validation, benchmarking, and evaluation frameworks for both traditional ML and generative AI systemsExperience implementing practical MLOps pipelines and AI operationalization frameworksStrong programming experience with: Python, Jupyter Notebooks or equivalent notebook environmentsExperience 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 deploymentsStrong communication and presentation skills with demonstrated customer-facing experienceAbility to translate complex technical concepts into actionable business and mission solutionsPreferred Qualifications:Master’s degree or PhDExperience supporting Federal Government, DoD, Intelligence Community, or highly regulated environmentsExperience implementing secure AI architectures in classified or sensitive environmentsExpertise 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 environmentsDemonstrated experience architecting and deploying enterprise-scale AI/ML solutions in production environmentsHands-on experience building and operationalizing:Agentic AI systems LLM-powered applications; AI orchestration frameworks; Autonomous decision-support systemsFamiliarity with AI security, adversarial AI, and zero trust principlesExperience with GPU infrastructure, model optimization, and scalable inference architecturesFamiliarity 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 capabilitiesLead technical discussions, architecture reviews, demonstrations, and customer briefings with confidence and authorityStay current with emerging AI research, industry trends, open-source technologies, and commercial AI platforms; continuously assess applicability to organizational and customer needsPublished research, conference presentations, patents, or contributions to the AI community preferredActive participation in AI research communities, industry working groups, or open-source AI initiativesMentor engineers, data scientists, and software developers on AI best practices, architectures, and implementation strategiesClearance RequirementActive Secret security clearance required, or ability to obtain and maintain a Secret clearance.Desired CharacteristicsStrategic thinker with strong technical depth and hands-on engineering capabilityPassion for continuous learning and staying ahead of rapidly evolving AI technologiesComfortable operating in ambiguous and fast-paced technical environmentsStrong leadership, collaboration, and mentoring abilitiesCustomer-focused with executive presence and consultative communication skillsTechnologies & ToolsExperience with several of the following is desired:PythonJupyter NotebookApache SparkDatabricksTensorFlowPyTorchHugging FaceLangChainSemantic KernelCrewAIAutoGenKubernetesDockerAzure AI ServicesAWS SageMakerGoogle Vertex AIVector databasesMLflowGitLab/GitHub CI/CD pipelinesWork 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.VTG’s estimated starting pay range is $120,000-$160,000 which is a general guideline for the geographic location. When extending an offer, VTG also considers work experience, education, skill level, market considerations and may possibly include contractual requirements which may cause an offer to fall outside of this range.