AI ML Data Scientist

  • REMOTE WORK, VA
  • Posted 10 hours ago | Updated 10 hours ago

Overview

Remote
On Site
USD 160,001.00 - 200,000.00 per year
Full Time

Skills

Security Clearance
Analytics
PaaS
Data Science
Use Cases
Modeling
Data Analysis
Training
Version Control
Continuous Integration and Development
Lifecycle Management
Amazon Lambda
Storage
Meta-data Management
Data Management
Promotions
Workflow
Large Language Models (LLMs)
Generative Artificial Intelligence (AI)
Documentation
Customer Experience
Computer Science
Cloud Computing
Amazon S3
Remote Desktop Services
Amazon RDS
Amazon SageMaker
Management
Databricks
Bitbucket
Programming Languages
SQL
Python
R
Apache Spark
Machine Learning (ML)
Data Security
Privacy
Regulatory Compliance
Continuous Integration
Continuous Delivery
Communication
Collaboration
Articulate
Amazon Web Services
Cloud Architecture
Artificial Intelligence
Information Technology
Systems Engineering
FOCUS

Job Details

Job ID:

Location: REMOTE WORK, VA, US

Date Posted: 2025-07-10

Category: Information Technology

Subcategory: Platform Engr

Schedule: Full-time

Shift: Day Job

Travel: No

Minimum Clearance Required: None

Clearance Level Must Be Able to Obtain: Public Trust

Potential for Remote Work: Yes

Description

SAIC is seeking an experienced AI/ML Engineer to help build and maintain the Analytics Application Platform (AAP), a full-fledged platform that provides both laboratory and factory services. AAP is designed as the IRS's primary AI/ML Platform-as-a-Service (PaaS), securely delivering mission-driven data science solutions at scale. This platform supports a wide range of use cases, from traditional model development to integrating Generative AI (GenAI) capabilities. As an AI/ML Engineer, you will play a crucial role in maturing the platform, ensuring it is production-ready, scalable, and compliant with IRS requirements, and you will support the platform regardless of the specific technologies or services being used, including Databricks and AWS SageMaker/Bedrock.

Key Responsibilities:
  • Develop and maintain robust data exploration and feature engineering pipelines to ensure data readiness for modeling within a secure and compliant infrastructure.
  • Implement and manage modern AI/ML tools such as Databricks, JupyterHub, AWS SageMaker, and Bedrock, for exploratory data analysis, AI design, model development, and training.
  • Integrate platform tools with TCloud Bitbucket for efficient version control, collaboration, and continuous integration/continuous deployment (CI/CD) processes.
  • Configure AWS S3 buckets for a Feature Store, ensuring compliance with IRS UNAX rules and maintaining distinct security contexts for different teams.
  • Establish and maintain a comprehensive model development pipeline utilizing MLflow for experiment tracking, model registry, and lifecycle management.
  • Create AWS Lambda functions and implement AWS Flow for efficient model artifact storage and metadata management.
  • Integrate with AWS RDS for robust data management and retrieval capabilities.
  • Configure SNS notifications to facilitate model promotion workflows.
  • Support teams in adhering to Responsible AI Principles by implementing the Responsible AI Toolbox, ensuring ethical and compliant AI/ML practices.
  • Leverage both Databricks and AWS services such as SageMaker and Bedrock to build and deploy large language models (LLMs), enabling IRS customers to create and integrate advanced Generative AI applications.
  • Ensure that all AI/ML development and deployment activities adhere to strict security and privacy standards, especially in compliance with IRS regulations.
  • Contribute to the iterative maturation of the platform, ensuring new capabilities are production-ready and scalable.
  • Develop support models, documentation, and processes that simplify the customer experience and enable their success in navigating the platform.
  • Work collaboratively to instill confidence in the platform, ensuring it goes beyond technical completeness to truly enable and scale AI/ML solutions.

Qualifications

Required:
  • Bachelor's or master's degree in Computer Science, Engineering, or a related field. A PhD is preferred.( 4 years experience in lieu of degree)
  • At least 9 years of experience in AI/ML, cloud services, and platform management, particularly with both Databricks and AWS (including S3, Lambda, RDS, SNS, SageMaker, and Bedrock).
  • Proven expertise in setting up and managing environments with tools such as Databricks, JupyterHub, MLflow, and Bitbucket.
  • Strong proficiency in programming languages and tools such as SQL, Python, R, and Spark. Familiarity with machine learning frameworks and libraries, including those used for building and deploying LLMs.
  • Deep understanding of data security and privacy, especially in compliance with IRS standards.
  • Experience with CI/CD pipelines and infrastructure as code.
  • Excellent communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to stakeholders.

Desired:
  • Previous experience working in a regulated environment, particularly within government agencies like the IRS.
  • Relevant certifications related to AWS or cloud architecture.
  • Knowledge of Responsible AI practices and principles.

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.


Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About SAIC