AI/ML ENGINEER

IQUASAR LLC•Fort Rucker, AL

4h•$100,000 - $130,000•Hybrid

About The Position

One of our clients is seeking an AI/ML Engineer to join their Engineering team responsible for the development, maintenance, and reliability of cloud-based applications on DoD platform environments.

Requirements

Minimum of 5 years of experience in relevant fields including IT security, data science, software engineering, design, development, or deployment of AI or machine learning systems in enterprise or Government environments
Experience working on data science, machine learning, or AI projects, either through internships, research projects, or professional roles.
Experience building, training, and deploying machine learning models and AI systems in a production environment.
Experience collaborating with cross-functional teams, including data scientists, software developers, and domain experts.
Experience in data collection, cleaning, and analysis techniques to prepare datasets for AI modeling.
Experience applying AI solutions to real-world problems in various enterprises and domains such as large corporations and Government agencies similar in size/scope to GSA, IRS, DoD or VA

Responsibilities

Design, develop, train, test, deploy, and maintain AI and machine learning models for enterprise-scale and Government applications.
Develop and operationalize production of AI/ML solutions, ensuring models and supporting systems are reliable, scalable, maintainable, and appropriate for VA mission requirements.
Collect, clean, transform, analyze, and prepare structured and unstructured data for AI/ML model development, training, testing, and evaluation.
Evaluate potential AI technologies, models, tools, frameworks, and architectures and recommend solutions appropriate for complex Federal Government and cybersecurity use cases.
Apply AI and machine learning techniques to solve real-world business, cybersecurity, engineering, analytics, and operational problems across a large enterprise environment.
Develop and support Generative AI and Large Language Model (LLM) solutions, including model configuration, system prompts, classifiers, fine-tuning, content moderation, safety filters, and other model controls.
Evaluate AI-generated outputs for accuracy, factuality, grounding, reliability, bias, helpfulness, honesty, and overall model performance before outputs are incorporated into VA efforts.
Design and execute AI/ML model evaluation and validation methodologies, including benchmark testing and comparative evaluation of model outputs.