Remote ML Engineer - AI Training & Inference

Synthires; San Francisco (CA); Remote; USD 83,000 - 165,000; Part time

Benefits offered by this job

Remote work

Flexible schedule

Output-based payment

15 hours/week

Job summary

Synthires is seeking an experienced ML Engineer (MSc. or PhD) for a remote, contractor role worldwide. The position focuses on developing and optimizing ML models, training pipelines, and inference systems with Python and reproducible workflows.

The role demands strong ML background, ability to implement and validate complex ML workflows, and a flexible schedule of approximately 15 hours per week. Immediate onboarding is preferred.

Qualifications

• Master's degree or PhD in Computer Science, Machine Learning, AI, Applied Mathematics, Statistics, Engineering, or a related quantitative field.
• Strong professional or research experience in machine learning.
• Proficiency in Python and experience using coding agents.
• Ability to implement, debug, and validate complex machine learning workflows.

Responsibilities

• Develop and validate machine learning models, training pipelines, and inference systems.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible workflows using Python and command-line tools.
• Debug numerical and system-level issues and optimize memory usage and performance.
• Create, solve, review, and validate challenging machine learning engineering tasks.

Skills

Python

Machine Learning

Coding agents

Education

Master's or PhD in CS/ML/AI

Tools

Command-line tools

NumPy/SciPy

TensorFlow/PyTorch

Job description

Synthires is seeking an experienced ML Engineer (MSc. or PhD) for a remote, contractor role worldwide. The position focuses on developing and optimizing ML models, training pipelines, and inference systems with Python and reproducible workflows.

The role demands strong ML background, ability to implement and validate complex ML workflows, and a flexible schedule of approximately 15 hours per week. Immediate onboarding is preferred.