ML Engineer: Production-Ready Models (Hybrid/Remote)

Garden Life Dev; Goldsboro (NC); Hybrid; USD 58,000 - 101,000; Full time

Benefits offered by this job

Health and welfare benefits

GLD assignment support

Job summary

Garden Life Development, LLC is seeking a Machine Learning Engineer for a full-time temporary assignment (W-2) in North Carolina. You will translate experiments into production, prepare data, train models, and deploy them with reliable monitoring.

This role requires Python, PyTorch or TensorFlow, and containerization experience. You will collaborate with cross-functional teams, document workflows, and support production systems across on-site, hybrid, or remote setups depending on the project.

Qualifications

• Experience in ML engineering or software engineering with ML.
• Proficiency in Python, PyTorch or TensorFlow, and containerization.
• Bachelor's degree in a related field, or an equivalent combination of education and experience. Degrees and certifications are verified before placement.

Responsibilities

• Implement and optimize machine learning models for business problems
• Gather requirements and design data-driven solutions with cross-functional teams
• Prepare and analyze large datasets for quality and relevance
• Select and apply algorithms and frameworks such as TensorFlow, PyTorch, or scikit-learn
• Deploy models into production and integrate with existing systems
• Monitor model performance and retrain or fine-tune as needed
• Document workflows and processes so results can be reproduced

Skills

ML engineering

Software engineering with ML

Python programming

Education

Bachelor's degree in a related field

Tools

Python

PyTorch

TensorFlow

scikit-learn

MLflow

Docker

Job description

Garden Life Development, LLC is seeking a Machine Learning Engineer for a full-time temporary assignment (W-2) in North Carolina. You will translate experiments into production, prepare data, train models, and deploy them with reliable monitoring.

This role requires Python, PyTorch or TensorFlow, and containerization experience. You will collaborate with cross-functional teams, document workflows, and support production systems across on-site, hybrid, or remote setups depending on the project.