ML Engineer for AI-Driven Manufacturing

GetJobSmart; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Forge Advanced Solutions in Austin, TX is seeking a Machine Learning Engineer for a full-time role focused on delivering AI-driven manufacturing solutions. You will design, train, and deploy models to optimize processes, handling data preprocessing, model development, and performance evaluation.

The ideal candidate holds a Master’s degree in CS/EE or a related field, with hands-on Python, TensorFlow, and PyTorch experience, plus strong problem-solving and communication skills in a dynamic

Qualifications

• Master's degree in Computer Science, Electrical Engineering, or a related field.
• 2+ years of experience in ML/AI with a strong project portfolio.
• Proficiency in Python and ML frameworks.
• Experience with data preprocessing and model deployment.

Responsibilities

• Develop and deploy machine learning models to solve complex problems in manufacturing.
• Collaborate with cross-functional teams to translate business needs into technical solutions.
• Design and implement scalable ML pipelines for data processing, model training, and deployment.
• Conduct data analysis and feature engineering to improve model performance.
• Optimize ML models for performance, accuracy, and efficiency.
• Stay up-to-date with the latest ML/AI advancements and apply them.
• Document work and share knowledge with the team through presentations.
• Contribute to best practices and standards for ML at Forge Advanced Solutions.

Skills

Python

Problem-solving

Communication

ML pipelines

Data analysis

AWS

GCP

Azure

Education

Master's degree in Computer Science, Electrical Engineering, or related field

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Forge Advanced Solutions in Austin, TX is seeking a Machine Learning Engineer for a full-time role focused on delivering AI-driven manufacturing solutions. You will design, train, and deploy models to optimize processes, handling data preprocessing, model development, and performance evaluation.

The ideal candidate holds a Master’s degree in CS/EE or a related field, with hands-on Python, TensorFlow, and PyTorch experience, plus strong problem-solving and communication skills in a dynamic