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# Machine Learning Engineer - USA | Remote

- **Company:** TRENT HOEK OUTDOORS LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Cerner, Amazon Web Services, Data Analysis, Microsoft Azure, Code Review, Computer Programming, Information Engineering, Data Structures, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Google Cloud, Pytorch, Keras, Information Technology
- **Published:** September 10, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pj2a24513l

## About the Role

Bachelor's degree in Computer Science, Data Science, Engineering, or a related field

Master's degree or PhD highly desirable

5+ years of experience in machine learning, data analysis, and predictive modeling

Proven experience with Cerner or Epic systems

Strong programming skills in Python, R, or other relevant languages

Familiarity with TensorFlow, Keras, or PyTorch

Strong understanding of machine learning algorithms and data structures

Experience with performance optimization techniques

Experience with AWS, Google Cloud, or Azure

Strong written and verbal communication skills

Ability to explain complex technical concepts to non-technical stakeholders

Ability to work independently and collaboratively

Ability to manage multiple tasks and projects

Healthcare industry experience is a plus

Skills & Requirements

Machine learning

Predictive modeling

Data analysis

Python

R

Cerner

Epic

TensorFlow

Keras

PyTorch

Machine learning algorithms

Data structures

Performance optimization

AWS, Google Cloud, or Azure

Healthcare data analysis

Data pipelines

Cross-functional collaboration

Code reviews

Technical documentation

Troubleshooting and problem solving

Machine learning research and innovation

## Description

The Consulting Machine Learning Engineer will design and implement machine learning solutions for complex healthcare problems. The role focuses on analyzing data from Cerner and Epic systems, developing predictive models, collaborating with data engineering and cross-functional teams, and supporting healthcare technology initiatives.


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