ML Engineer
About The Company Jobrapido connects professionals with career opportunities across industries and locations. For this remote, project-based opportunity, Jobrapido is seeking an experienced Machine Learning Engineer to contribute to AI training projects. The work focuses on building and improving machine learning systems, developing challenging engineering tasks, and evaluating solutions for technical quality. Successful candidates will bring strong quantitative foundations, practical coding skills, and the ability to deliver reliable work independently in a distributed environment. About The Role As a Machine Learning Engineer, you will work on coding-intensive projects involving model development, training and inference systems, data processing, and performance optimization. You will use Python and command-line tools to implement, test, and document reproducible workflows. The role also involves creating, solving, reviewing, and validating complex machine learning engineering tasks, including work designed to assess or improve AI systems. This is a remote contractor position open to candidates worldwide. The expected commitment is approximately 15 hours per week, with a flexible schedule. Compensation is $60–$120 per hour, depending on relevant expertise and project requirements. Payment is output-based for tasks that meet the defined project specifications. Immediate availability is preferred, as the first task is expected to begin within 24–48 hours after onboarding.
Qualifications
A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or another related quantitative discipline is required. Candidates should have substantial professional or research experience in machine learning and practical proficiency in Python. Experience using coding agents is also required. You should be comfortable implementing, debugging, and validating complex machine learning workflows. Strong analytical skills, attention to technical detail, and the ability to investigate numerical or system-level problems are important. Candidates must be able to communicate technical decisions clearly, work independently, and produce dependable results in a remote setting. Experience at an established technology company, AI laboratory, or research organization is preferred. Exceptional academic achievements or open-source engineering contributions that demonstrate relevant machine learning expertise are also valued.
Responsibilities
Develop and validate machine learning models, training pipelines, and inference systems. Implement model components, data pipelines, evaluation systems, and numerical methods in Python. Build reproducible workflows using appropriate command-line tools, and ensure that experiments and outputs can be checked and repeated. Debug numerical and system-level issues, identify sources of errors or inefficiency, and optimize memory usage and overall performance. Create, solve, review, and validate challenging machine learning engineering tasks, applying sound technical judgment to assess correctness and quality. Follow project specifications, document relevant findings, and deliver work within agreed timelines.
Benefits
This opportunity offers remote work from anywhere in the world, a flexible part-time schedule, and an hourly rate of $60–$120. You will contribute to practical AI training projects involving model development and engineering evaluation. The contractor arrangement provides the opportunity to apply specialized expertise to defined tasks without a full-time schedule. Project payment is tied to completed outputs that satisfy the stated requirements. The selection process includes an application and screening questions, an approximately 30-minute AI interview, and a hiring manager review. Candidates who are selected will complete onboarding before beginning their first task. Equal Opportunity Jobrapido welcomes applications from qualified candidates worldwide. Hiring decisions are based on relevant qualifications, skills, experience, and project needs. Applicants should be able to meet the role’s technical requirements and contribute respectfully and professionally in a remote working environment.