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.
Key Responsibilities
AI/ML Solution Development
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.
Local and On-Premises AI Infrastructure
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.
Azure Government AI Platforms
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.
Data Engineering and Analytics
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.
MLOps and DevSecOps
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.
Stakeholder Support
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
Education
Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related field.
Master's degree preferred.
Professional Experience
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.
Experience supporting secure government, defense, or regulated environments preferred.
Technical Skills
Machine Learning & Data Science
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.
Generative AI & LLMs
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
Azure Government and Cloud AI
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 deploying AI workloads in Azure Government environments preferred.
Local AI Infrastructure
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.
Data Platforms
SQL and relational databases
Data warehousing concepts
ETL/ELT pipeline development
Vector databases and semantic search platforms
Software Engineering
Git-based development workflows
REST APIs and microservices
CI/CD pipelines
Infrastructure-as-Code concepts
Preferred Qualifications
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.
Desired Technologies
Candidates should have experience with several of the following:
Programming
Python
SQL
PowerShell
Bash
AI/ML Frameworks
PyTorch
TensorFlow
Scikit-learn
Hugging Face Transformers
LLM Ecosystem
LangChain
LlamaIndex
Semantic Kernel
OpenAI APIs
Azure OpenAI APIs
Infrastructure
Docker
Kubernetes
AKS
Linux
GitHub Actions
Azure DevOps
Databases
PostgreSQL
SQL Server
Vector databases
Azure Data Services
Security Requirements
U.S. citizenship required.
Ability to pass government background investigation.
Ability to comply with all applicable government security and information assurance requirements.
Success Criteria
Within the first 12 months, the selected candidate will:
Deploy and support production AI solutions in Azure Government.
Establish repeatable MLOps processes for AI model deployment and maintenance.
Deploy and manage secure local/open-source LLM environments.
Develop mission-focused AI applications leveraging RAG and agentic workflows.
Improve operational efficiency through automation and advanced analytics.
Due to the nature of the government contract requirements and/or clearances requirements, US citizenship is required.
Navarro is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, race, religion, color, national origin, age, disability, veteran’s status, or any classification protected by applicable state or local law.