Senior Data Scientist – AI Engineer

This is a fully remote position, open to applicants in Tennessee.

📋 Description

• Design, develop, train, assess, and implement machine learning and generative AI solutions.

• Create and sustain predictive analytics, natural language processing, computer vision, and LLM-based applications.

• Execute Retrieval-Augmented Generation (RAG), agentic workflows, and knowledge management systems.

• Analyze commercial, open-source, and bespoke AI models for specific mission use cases.

• Deploy and manage local/open-source models in secure settings.

• Configure and fine-tune inference environments utilizing GPUs and containerized deployments.

• Oversee model serving platforms and inference frameworks.

• Implement monitoring, performance optimization, and lifecycle management for locally hosted models.

• Provide support for disconnected, restricted, or air-gapped operational contexts.

• Design and implement AI solutions within Azure Government.

• Construct and manage solutions leveraging Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Azure Kubernetes Service (AKS), and associated services.

• Establish secure model deployment, monitoring, and governance controls.

• Integrate AI services with enterprise systems and data platforms.

• Develop data pipelines that support AI and analytics workloads.

• Conduct data exploration, feature engineering, model evaluation, and performance assessment.

• Work with structured, semi-structured, and unstructured data sources.

• Ensure data quality, lineage, and governance standards are upheld.

• Implement CI/CD pipelines for machine learning and AI workloads.

• Create automated testing, validation, and deployment processes.

• Set up model monitoring, drift detection, and performance reporting.

• Apply security measures and compliance requirements throughout the AI lifecycle.

• Collaborate with mission owners, analysts, engineers, cybersecurity teams, and leadership.

• Translate operational needs into technical AI solutions.

• Prepare technical documentation, architecture diagrams, and presentations.

⛳️ Requirements

• Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field.

• Master's degree is preferred.

• Over 5 years of experience in data science, machine learning, AI engineering, or related domains.

• At least 2 years of experience in deploying and managing production AI/ML systems.

• Experience in supporting secure government, defense, or regulated environments is preferred.

• Strong understanding of supervised and unsupervised learning techniques.

• Experience with model development, evaluation, and optimization.

• Proficient in statistical analysis and experimental design.

• Expertise in Python and popular ML frameworks.

• Experience in deploying and operating open-source LLMs.

• Familiarity with:

• - Llama family models

• - Mistral models

• - Hugging Face models

• Knowledge of:

• - RAG architectures

• - Agent frameworks

• - Prompt engineering

• - Model evaluation methodologies

• - Fine-tuning techniques

• 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 in deploying AI workloads in Azure Government environments is preferred.

• Familiarity with:

• - Docker

• - Kubernetes

• - GPU-based inference systems

• - vLLM, Ollama, TGI, or similar inference platforms

• - Linux administration

• Understanding of model quantization and performance optimization strategies.

• Knowledge of SQL and relational databases.

• Familiarity with data warehousing concepts.

• Experience in ETL/ELT pipeline development.

• Knowledge of vector databases and semantic search platforms.

• Proficiency in Git-based development workflows.

• Experience with REST APIs and microservices.

• Knowledge of CI/CD pipelines.

• Familiarity with Infrastructure-as-Code principles.

• Active security clearance or the ability to obtain one.

• Experience with the NIST AI Risk Management Framework.

• Familiarity with FedRAMP, RMF, or government cybersecurity compliance frameworks.

• Experience supporting classified or controlled environments.

• Relevant Azure certifications.

• Experience with distributed GPU environments.

• Experience in implementing AI governance and responsible AI controls.

• Candidates should possess experience with several of the following:

• - Python

• - SQL

• - PowerShell

• - Bash

• - PyTorch

• - TensorFlow

• - Scikit-learn

• - Hugging Face Transformers

• - LangChain

• - LlamaIndex

• - Semantic Kernel

• - OpenAI APIs

• - Azure OpenAI APIs

• - Docker

• - Kubernetes

• - AKS

• - Linux

• - GitHub Actions

• - Azure DevOps

• - PostgreSQL

• - SQL Server

• - Vector databases

• - Azure Data Services

🏝️ Benefits

• Health Care Plan (Medical, Dental & Vision)

• Retirement Plan (401k)

• Life Insurance (Basic, Voluntary & AD&D)

• Paid Time Off (Vacation & Public Holidays)

• Short Term & Long Term Disability