Scientific Programmer IV

Cherokee Federal

About The Position

Cherokee Nation System Solutions, LLC is seeking a visionary Cloud Data & AI/ML Architect to lead the strategic design and modernization of enterprise data and AI platforms in complex cloud environments. This senior role requires expertise in cloud architecture, advanced data platform design, and AI/ML strategy to build scalable, secure, and intelligent systems for high-performance computing, advanced analytics, operational efficiency, and machine learning. This position requires an active Public Trust clearance or the ability to obtain a Public Trust clearance to be considered.

Requirements

Coding/Scripting: Python (NumPy, Pandas); R ecosystem (tidyverse, ggplot2), experience with libraries/frameworks such as PyTorch, TensorFlow, Scikit-Learn.
AI/ML: Experience with Computer Vision, NLP, Large Language Models (LLMs), and core algorithms (Linear Regression, Decision Trees, Clustering).
Cloud & DevOps: Hands-on experience in Azure (preferred) and/or AWS; containerization (Docker), orchestration (Kubernetes), Infrastructure-as-Code (Terraform, Ansible).
MLOps: Model deployment, pipeline automation, monitoring, and lifecycle management (e.g., Azure ML Studio or similar platforms).
Operating Systems: Strong proficiency in Linux (command line, file systems, permissions, shell scripting).
Tools: Jupyter Notebook, VSCode, Git (version control and collaboration).
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
Strong experience with cloud platforms (AWS, Azure, GCP).
Hands-on experience with modern data platforms
Experience designing and supporting AI/ML workflows and platforms.
Must pass pre-employment requirements of Cherokee Federal.

Nice To Haves

Experience with Azure preferred - all acceptable if well-versed in cloud technologies
Experience building enterprise AI/ML platforms or centers of excellence.
Domain expertise in scientific, or large-scale enterprise data systems.
Knowledge of data governance, security, and compliance frameworks is preferred but not required.
Mathematics or Statistics background is preferred but not required.

Responsibilities

Architect modern data platforms (data lakes, lakehouses, warehouses) to support analytics and AI/ML workloads.
Define and implement enterprise AI/ML platform strategy, including model lifecycle, feature stores, and deployment pipelines.
Establish AI/ML architecture standards, patterns, and best practices.
Collaborate with scientists and IT to align data and AI capabilities with organizational goals.
Provide technical leadership, mentorship, and architectural guidance to engineering and data science teams.
Develop and optimize algorithms for high-performance computing environments.
Design scalable data pipelines for scientific datasets.
Architect containerized scientific workflows.
Build, train, and deploy machine learning models, Work with large-scale datasets for predictive modeling, Optimize model performance in distributed environments
Performs other job-related duties as assigned