Senior Data Scientist / AI Engineer (3878)

Navarro Inc.•Oak Ridge, TN

1d•Remote

About The Position

Navarro Research and Engineering is recruiting a Senior Data Scientist / AI Engineer. 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.

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 Haves

Master's degree preferred.
Experience supporting secure government, defense, or regulated environments preferred.
Experience deploying AI workloads in Azure Government environments preferred.
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.
Experience with: LangChain, LlamaIndex, Semantic Kernel, OpenAI APIs, Azure OpenAI APIs.
Experience with: GitHub Actions, Azure DevOps.
Experience with: PostgreSQL, SQL Server.
Experience with: Azure Data Services.

Responsibilities

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.