Data Scientist, Databricks, Mosaic AI

OPENDataJobs

. Build, evaluate, and put machine learning and generative AI models into production for a federal agency .

Posted 11/3/2026full-timeRemote • Virginia • United StatesMid-LevelSenior💰 $110,000 - $140,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning models in production environments, particularly using Azure Databricks and MLflow for tracking and evaluation. Proficient in developing LLM applications and ensuring model quality through rigorous evaluation and monitoring processes.

Highest-signal resume keywords

Machine Learning EngineeringAzure DatabricksMLflowPython for Data ScienceModel Deployment and Monitoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningGenerative AIPythonPandasScikit-LearnPySparkSQLGitModel EvaluationRetrieval-Augmented Generation

Soft Skills

CollaborationDocumentation WritingCommunication

Tools & Technologies

Azure DatabricksMLflowDatabricks Feature StoreDatabricks Model ServingAgent BricksDatabricks AI SearchMicrosoft Foundry

Certifications & Qualifications

Databricks CertificationMicrosoft Azure AI CertificationData Science Certification

Industry Keywords

Federal GovernmentImpact Level 5 (IL-5)Model Risk ManagementModel ValidationAI-Assisted Developer Tooling

Tech Stack

Tools & technologies

AzurePandasPySparkPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Build, evaluate, and put machine learning and generative AI models into production for a federal agency
Develop and train machine learning models on Azure Databricks
Track experiments, models, and versions in MLflow
Build reusable features in the Databricks Feature Store
Serve models through Databricks Model Serving
Build retrieval and agent applications with Agent Bricks and Databricks AI Search using Azure OpenAI models through Microsoft Foundry
Evaluate model and agent quality with MLflow evaluation, LLM judges, labeled test sets, and human review
Monitor production models for drift and quality
Write documentation requested by model reviews
Measure model quality before and after release
Record each model's purpose and limitations
Leave maintainable pipelines that teams can retrain and rerun
Collaborate with developers, engineers, data scientists, architects, and strategists across strategy and implementation work
Help develop the firm's capabilities, tools, and lines of business

Requirements

What you’ll need

4+ years of data science or machine learning engineering experience, including models deployed to production
Bachelor's degree
Python for data science and machine learning, including pandas, scikit-learn, and PySpark
Hands-on Azure Databricks work, including MLflow for experiment tracking and model management
Deploying and monitoring models in production, including model serving, versioning, and drift monitoring
Building LLM applications, including retrieval-augmented generation (RAG)
Evaluating model and LLM output against defined metrics, test sets, and human review
Structured Query Language (SQL) and Git-based version control
Delivery experience in a federal government environment, working to its security, access, and review processes
Proficiency in writing, PowerPoint, and Excel
United States citizenship; dual citizenship and green card holders are prohibited by the contract terms
Ability to satisfy the required suitability, security, and access requirements
Preferred: Experience on a federal system accredited at Impact Level 5 (IL-5) or higher
Preferred: Agent Bricks, Databricks AI Search (formerly Vector Search), or MLflow 3 evaluation for generative AI
Preferred: Experience with a second managed machine-learning platform, such as Azure Machine Learning, Amazon SageMaker, or Google Vertex AI
Preferred: Azure OpenAI or other models in Microsoft Foundry
Preferred: Databricks certification, or a Microsoft Azure AI or data science certification
Preferred: Model risk management or model validation experience, including documentation a model review asks for
Preferred: Familiarity with artificial intelligence (AI)-assisted developer tooling

Benefits

Comp & perks

Medical, dental, and vision with the employee premium fully paid and half of dependent premiums
Employer-paid life, accidental death, and short-term and long-term disability insurance
401(k) with an employer match of up to 4% of salary
Unlimited paid time off
Sponsored professional certifications and continuing education
Extensive onboarding
Rotation across functions to expand skills and perspective