Senior Machine Learning Engineer (MSc. / PhD)
Location: Global — fully remote
Employment: Independent contractor
Work commitment: Approximately 15 hours per week
Compensation: $60–$120 per hour, output-based
About the Opportunity
Contribute to an AI research and technology initiative advancing next-generation AI models and agents. Work includes developing technical evaluations, improving model performance, and building reliable training and inference workflows.
Role Overview
Develop, implement, review, and validate complex machine learning engineering solutions. The role requires strong Python skills, practical machine learning experience, and hands-on use of coding agents in development workflows. It suits professionals who enjoy complex technical problem-solving, model optimization, and producing reliable, reproducible code.
Key Responsibilities
- Develop and validate machine learning models, training pipelines, and inference systems.
- Implement model components, data pipelines, evaluation frameworks, and numerical methods.
- Build reproducible workflows using Python and command-line tools.
- Debug algorithmic, numerical, and system-level issues.
- Optimize memory use, computational efficiency, and inference throughput.
- Create, solve, review, and validate machine learning engineering tasks.
- Integrate coding agents into Python development workflows.
- Verify correctness, reproducibility, and performance against defined criteria.
- Review code quality, technical accuracy, and adherence to specifications.
Required Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a related quantitative discipline.
- Strong professional or research experience in machine learning.
- Demonstrated proficiency in Python.
- Practical experience using coding agents in Python development workflows.
- Hands-on experience developing, implementing, debugging, or optimizing machine learning models.
- Strong analytical, problem-solving, and technical reasoning skills.
- Ability to work independently and deliver high-quality technical solutions.
Preferred Qualifications
- Experience at a technology company, AI research lab, research organization, or recognized engineering environment.
- Experience with PyTorch, TensorFlow, or JAX.
- Familiarity with model training, inference optimization, numerical computing, and performance profiling.
- Experience with GPU computing, memory optimization, or high-throughput inference.
- Academic publications, research projects, or open-source contributions. Exceptional academic or open-source experience may also be considered.
Work Arrangement
Fully remote; candidates worldwide may apply. Flexible schedule, with candidates choosing their working hours and days, including weekends. Approximately 15 hours per week. Independent contractor arrangement; immediate joiners preferred.
Compensation
$60–$120 per hour, subject to an output-based payment structure. Payments depend on tasks meeting project specifications; time requirements vary based on task complexity, expertise, and workflow efficiency. Minimum submission requirements apply.
Selection Process
- Application submission and screening questions.
- AI-powered interview of approximately 30 minutes.
- Hiring manager review.
- Onboarding and initial task assignment.
The process moves quickly, and successful candidates may be expected to begin their first task within 24–48 hours after onboarding.