Remote Machine Learning Engineer
Confirmed on the employer's own hiring board on Sep 28, 2026. First seen by Alion on Jul 28, 2026.
We're looking for a Machine Learning Engineer to help build and improve AI-powered products. You'll work with large datasets, train and evaluate machine learning models, and collaborate with software engineers to bring models into production.
This is a great opportunity for someone who enjoys solving practical problems with machine learning and wants to work on real-world AI applications.
What you'll do
Develop, train, and evaluate machine learning models.
Prepare and analyze datasets for model training.
Improve model performance through experimentation and testing.
Deploy and maintain ML models in production environments.
Collaborate with software engineers to integrate ML solutions into products.
Monitor model performance and continuously improve accuracy.
Stay up to date with new machine learning techniques and technologies.
What we're looking for
Basic understanding of machine learning concepts and algorithms.
Experience with Python.
Familiarity with machine learning libraries such as PyTorch, TensorFlow, or scikit-learn.
Comfortable working with data and writing clean, maintainable code.
Familiarity with Git.
Good problem-solving skills.
Strong written and verbal English communication.
Nice to have
Experience with large language models (LLMs).
Experience with cloud platforms such as AWS, GCP, or Azure.
Familiarity with SQL.
Experience deploying ML models.
Personal projects or open-source contributions related to AI or machine learning.
Requirements
1+ year of experience in machine learning, software engineering, data science, or a related technical role or strong personal projects demonstrating ML skills.
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field is a plus, but not required.
Passion for learning and building AI solutions.
What we offer
Fully remote work.
Flexible working environment.
Opportunity to work on real AI products.
Challenging technical problems with room to grow.
Collaborative and fast-moving team.
Competitive compensation based on experience.