Data Scientist (AI / ML) | SME

Amatriot Group, LLC; Chantilly (VA); On-site; USD 130,000 - 200,000; Full time

Job summary

Amatriot Group, LLC in Chantilly, VA seeks a Data Scientist (AI/ML) to build ML models, analytics solutions, and generative AI capabilities supporting intelligent products and data-driven decisions.

You will lead the full model lifecycle, from exploration and feature engineering to production-ready deployment, collaborating with data engineering, product, and MLOps teams to deliver actionable stakeholder insights.

Qualifications

• Design and develop machine learning models and analytics solutions for AI-powered products.
• Implement generative AI techniques and fine-tune large language models (LLMs).
• Create retrieval-augmented generation (RAG) workflows for enhanced analytics.

Responsibilities

• Develop ML models, analytics solutions, and AI capabilities across the product lifecycle.
• Integrate generative AI into intelligent products and analytics applications; perform LLM fine-tuning and prompt engineering.
• Establish robust experimental designs and monitor model fairness and governance throughout development.
• Collaborate with data engineering, product, and MLOps teams to deploy production-ready systems and translate results into actionable insights.

Skills

ML models

Generative AI

LLM fine-tuning

Prompt engineering

RAG workflows

Model governance

Stakeholder communication

Job description

Location: Chantilly, VA
Security Clearance: Active TS or higher [Required]
Job Type: Full-Time
Target Salary Range*:$130,000 - $200,000

*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

Position Overview

The Data Scientist (AI / ML) develops machine learning models, advanced analytics solutions, and generative AI capabilities supporting intelligent products and data-driven decision-making. This role spans the full model lifecycle, from data exploration and feature engineering through validation and refinement. Working with data engineering, product, and MLOps teams, the scientist translates complex algorithmic outcomes into production-ready systems and actionable stakeholder insights.

Key Responsibilities

Machine Learning and Advanced Analytics

• Develop machine learning models and advanced analytics solutions.
• Perform data exploration, feature engineering, model validation, and refinement.
• Prototype scalable predictive, classification, and optimization solutions.

Generative AI Development

• Integrate modern generative AI techniques into intelligent products and analytical solutions.
• Perform large language model (LLM) fine-tuning and prompt engineering.
• Develop retrieval-augmented generation (RAG) workflows.

Experimental Design and Model Governance

• Establish rigorous experimental designs to support model development and evaluation.
• Monitor model fairness and governance throughout the model lifecycle.

Collaboration and Production Integration

• Partner with data engineering, product, and MLOps teams to translate algorithmic outcomes into production-ready systems.
• Communicate complex analytical results as actionable stakeholder insights.