AI Developer - Fully Remote (U.S. Based)

MRIoA•Salt Lake, UT

1d•Remote

About The Position

MRIoA is seeking a skilled and forward-thinking AI Developer to lead the design, development, and deployment of applications (including AI/ML solutions), using coding assistants, across the enterprise. This role requires a strong understanding of AI, machine learning, data preparation, and model training/fine-tuning. The ideal candidate will work closely with cross-functional teams and external partners to identify opportunities for AI/ML adoption and deliver innovative, scalable solutions that align with our business goals and compliance standards.

Requirements

3+ years of experience developing Artificial Intelligence (AI) models
3+ years of experience developing Machine Learning (ML) models
3+ years of experience deploying AI models in production environments
3+ years of experience deploying ML models in production environments
Experience with AI/ML libraries such as TensorFlow, PyTorch, and scikit-learn
Experience deploying AI/ML models on cloud platforms (AWS, Azure, or GCP)
Experience in one or more AI/ML domains such as NLP, computer vision, or time series forecasting
Bachelor’s degree in Computer Science, or a related field

Nice To Haves

Experience working in healthcare
Proficiency in Python
Proficiency in Node.js
Master’s degree in Computer Science, or a related field

Responsibilities

Collaborate with business, operations, and technology teams to define solution for AI use cases and align solution delivery timelines.
Partner with internal teams and third-party vendors to develop AI systems that are efficient, compliant, and scalable.
Lead rapid prototyping efforts to demonstrate the value of AI/ML applications and inform broader adoption.
Stay current with emerging AI/ML trends and technologies; contribute to the organization’s long-term AI strategy.
Research, design, and implement machine learning models (supervised, unsupervised, reinforcement learning), including deep learning and NLP.
Conduct data preparation, cleansing, and feature engineering to support AI/ML workflows.
Train, validate, and fine-tune models to optimize performance, accuracy, and efficiency.
Build reusable, production-ready pipelines for AI model deployment using MLOps best practices.
Collaborate with application development team to integrate AI/ML capabilities into existing products and platforms.
Design and implement robust testing and evaluation frameworks for model validation.
Monitor, maintain, and continuously improve deployed models to ensure business relevance and performance.
Ensure all AI systems are secure and compliant with regulatory standards (e.g., HITRUST, SOC 2, HIPAA).
Support transition of business processes to AI-driven solutions by partnering with operations, business, training, communications, and customer success teams.
Provide clear documentation, materials, and support to promote user adoption of AI tools.
Conduct retrospectives to capture lessons learned and incorporate continuous improvements.