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Navarro Research and Engineering is recruiting a Senior Data Scientist / AI Engineer (3878). This is a remote position. Citizenship is required. Navarro Research & Engineering is an award-winning federal contractor dedicated to partnering with clients to advance clean energy and deliver effective solutions for complex challenges in the nuclear and environmental fields. Joining Navarro means being a part of an exceptional team committed to quality and safety while also looking for innovative strategies to create value for the client's success. Headquartered in Oak Ridge, Tennessee, Navarro has active programs in place across the nation for DOE/NNSA, NASA, and the Department of Defense. We are seeking a Senior Data Scientist / AI Engineer to design, develop, deploy, and maintain machine learning and generative AI solutions within a government environment. This role will support both locally hosted AI systems and cloud-based AI services within Microsoft Azure Government, including Azure AI Foundry and related Azure AI services. The ideal candidate has hands-on experience building production AI systems, deploying and operating open-source large language models (LLMs), implementing secure MLOps practices, and developing AI applications that meet government security and compliance requirements.
Job Responsibility
Design, build, train, evaluate, and deploy machine learning and generative AI solutions
Develop and maintain predictive analytics, NLP, computer vision, and LLM-based applications
Implement Retrieval-Augmented Generation (RAG), agentic workflows, and knowledge management solutions
Evaluate commercial, open-source, and custom AI models for mission-specific use cases
Deploy and operate local/open-source models in secure environments
Configure and optimize inference environments using GPUs and containerized deployments
Manage model serving platforms and inference frameworks
Implement monitoring, performance tuning, and lifecycle management for locally hosted models
Support disconnected, restricted, or air-gapped operational environments
Design and deploy AI solutions within Azure Government
Build and manage solutions using Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Azure Kubernetes Service (AKS), and related services
Implement secure model deployment, monitoring, and governance controls
Integrate AI services with enterprise systems and data platforms
Develop data pipelines supporting AI and analytics workloads
Perform data exploration, feature engineering, model evaluation, and performance analysis
Work with structured, semi-structured, and unstructured data sources
Ensure data quality, lineage, and governance standards are maintained
Implement CI/CD pipelines for machine learning and AI workloads
Develop automated testing, validation, and deployment processes
Establish model monitoring, drift detection, and performance reporting
Apply security controls and compliance requirements throughout the AI lifecycle
Collaborate with mission owners, analysts, engineers, cybersecurity personnel, and leadership
Translate operational requirements into technical AI solutions
Prepare technical documentation, architecture diagrams, and presentations
Requirements
Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related field
5+ years of experience in data science, machine learning, AI engineering, or related fields
2+ years of experience deploying and operating production AI/ML systems
Strong knowledge of supervised and unsupervised learning techniques
Experience with model development, evaluation, and optimization
Statistical analysis and experimental design experience
Proficiency in Python and common ML frameworks
Experience deploying and operating open-source LLMs
Experience with Llama family models, Mistral models, Hugging Face models
Knowledge of RAG architectures, Agent frameworks, Prompt engineering, Model evaluation methodologies, Fine-tuning approaches
Experience with Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure Kubernetes Service (AKS), Azure Storage and Data Services, Azure Identity and Access Management
Experience with Docker, Kubernetes, GPU-based inference systems, vLLM, Ollama, TGI, or similar inference platforms, Linux administration
Understanding of model quantization and performance optimization techniques
SQL and relational databases
Data warehousing concepts
ETL/ELT pipeline development
Vector databases and semantic search platforms
Git-based development workflows
REST APIs and microservices
CI/CD pipelines
Infrastructure-as-Code concepts
U.S. citizenship required
Ability to pass government background investigation
Ability to comply with all applicable government security and information assurance requirements
Nice to have
Active security clearance or ability to obtain one
Experience with NIST AI Risk Management Framework
Experience with FedRAMP, RMF, or government cybersecurity compliance frameworks
Experience supporting classified or controlled environments
Azure certifications
Experience with distributed GPU environments
Experience implementing AI governance and responsible AI controls
Master's degree preferred
Experience supporting secure government, defense, or regulated environments preferred
Experience deploying AI workloads in Azure Government environments preferred