- Senior Machine Learning Engineer - Remote
- Role Overview
Job Type: Contract
Work Arrangement: Fully Remote, Global
Work Schedule: Flexible, approximately 15 hours per week
Compensation: $57,600–$115,200 annualized equivalent ($60–$120 per hour)
Education: Master’s degree or PhD
About the Role
We are seeking an experienced Senior Machine Learning Engineer to contribute to AI training projects involving model development, training and inference systems, numerical computing, performance optimization, and Python engineering.
This is a highly technical, coding-intensive role focused on creating, solving, reviewing, and validating challenging machine learning engineering tasks. You will build and debug implementations, develop reproducible workflows, optimize system performance, and verify results against objective correctness and performance requirements.
Key Responsibilities
Develop and validate machine learning models, training pipelines, inference systems, and supporting infrastructure.
Implement model components, data pipelines, evaluation systems, and numerical methods.
Build reproducible workflows using Python and command-line tools.
Debug numerical, software, and system-level failures.
Optimize memory usage, computational throughput, and implementation performance.
Review and validate engineering solutions against defined specifications.
Use coding agents as part of your Python development workflow.
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Required Qualifications
Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
Strong professional or research experience in machine learning.
Practical proficiency in Python and coding agents.
Ability to develop, debug, and validate complex code-based solutions independently.
Strong analytical skills and attention to technical correctness.
Preferred Qualifications
Experience at an established technology company, AI laboratory, research organization, or recognized engineering environment.
Exceptional academic research or open-source contributions demonstrating relevant engineering expertise.
Experience with model training and inference, numerical computing, performance optimization, or reproducible machine learning workflows.
Compensation
Compensation is output-based, with payment for each task that meets project specifications. Task completion time may vary depending on experience and workflow. Minimum submission requirements apply.
The stated hourly rate of $60–$120 corresponds to an annualized equivalent of $57,600–$115,200, based on 1,920 working hours per year. This is a comparison figure only; the role is approximately 15 hours per week and pays per accepted task.
Selection Process
Submit an application and complete the screening questions.
Complete an AI interview of approximately 30 minutes.
Participate in a hiring manager review.
Start Timeline
Candidates should be ready to begin promptly. Selected candidates are expected to start their first task within 24–48 hours after completing onboarding.
