Machine Learning Engineer - Remote at YO AI Labs

About this role

Job Description: Junior Machine Learning Engineer Location: Global, Fully Remote Job Type: Contractor Time Commitment: Approximately 15 hours per week Schedule: Flexible – choose your preferred working days and hours, including weekends. About the Role We are seeking skilled Machine Learning Engineers to contribute to an AI training project focused on model development, training and inference systems, numerical computing, performance optimization, and Python-based engineering. This is a highly technical, coding-intensive role. You will create, solve, review, and validate challenging machine learning engineering tasks. Projects may involve implementing or modifying models, building reproducible training and inference workflows, optimizing memory usage and throughput, debugging numerical or system-level issues, and validating solutions against objective correctness and performance requirements. Candidates must have practical experience using coding agents as part of their Python development workflow. Key
Develop and validate machine learning models, training pipelines, inference systems, and supporting infrastructure.
Implement model components, data pipelines, evaluation systems, and numerical computing methods.
Build reproducible workflows using Python and command-line tools.
Debug and resolve numerical, performance, and system-level engineering issues.
Optimize model performance, memory usage, and computational efficiency.
Review and validate machine learning implementations against defined technical requirements.
Required Qualifications
Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative field.
Strong professional or research experience in machine learning.
Advanced practical proficiency in Python programming.
Hands-on experience using coding agents within Python development workflows.
Ability to independently develop, debug, and validate complex technical solutions.
Experience with equivalent tools may also be considered when supported by directly relevant technical expertise. Preferred Background
Experience at an established technology company, AI laboratory, research organization, or recognized engineering environment.
Exceptional open-source contributions or academic research experience.
Practical experience with model training, inference optimization, numerical computing, and machine learning infrastructure.
Selection Process
Submit an application and complete the screening questions.
Complete an AI interview lasting approximately 30 minutes.
Proceed through the hiring manager review.
Originally posted on Himalayas