Machine Learning Applied Scientist

OpenTrain AI, Inc.; United States; Remote; USD 83,000 - 165,000; Part time

Job summary

OpenTrain AI, Inc. is seeking a part-time remote machine-learning engineer to develop and validate models, training pipelines, and inference systems.

You will work on numerical methods and software components in a coding-heavy environment, deploying in a flexible 15-hour-per-week schedule. The role requires a master’s or PhD in a quantitative field, strong Python experience, and familiarity with PyTorch, NumPy, SciPy, and related tools.

Qualifications

• Master's degree or PhD in a quantitative field (CS/ML/AI/Applied math/Statistics/Engineering)
• Strong professional or research experience in machine learning and practical proficiency with Python
• Experience with ML frameworks and numerical computing tools is highly desirable

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 with Python and command-line tools.
• Optimize memory use and throughput; debug numerical or system-level failures; verify technical results.
• Use coding agents in a coding-heavy workflow.

Skills

Python

Machine learning

PyTorch

JAX

NumPy

SciPy

llama.cpp

tokenizers

transformers

vLLM

SGLang

Open-source

Education

Master's degree or PhD in CS/ML/AI/applied math/statistics/engineering

Tools

PyTorch

JAX

NumPy

SciPy

tokenizers

transformers

Job description

Build and validate machine-learning models, training pipelines, inference systems, and numerical methods remotely for about 15 flexible hours per week. Compensation is $60 to $120 per hour equivalent, paid per task that meets the project specifications.

$60–$120/hr

equivalent, paid per accepted task

Contract, part-time

Engagement

Remote

Location

• Algeria
• Argentina
• Austria
• Bahrain
• Bangladesh
• Belgium
• Brazil
• Canada
• Chile
• Colombia
• Denmark
• Egypt
• France
• Germany
• Ghana
• Greece
• India
• Indonesia
• Italy
• Japan
• Jordan
• Kazakhstan
• Kenya
• Kuwait
• Kyrgyzstan
• Lebanon
• Malaysia
• Mexico
• Morocco
• Netherlands
• Nigeria
• Oman
• Pakistan
• Palestine
• Peru
• Philippines
• Portugal
• Qatar
• Saudi Arabia
• Singapore
• South Africa
• Spain
• Sri Lanka
• Switzerland
• Taiwan
• Thailand
• Tunisia
• United Arab Emirates
• United States
• Uzbekistan
• Vietnam

The work

You will create, solve, review, and validate machine-learning engineering tasks against correctness and performance requirements. The work combines model development, software implementation, numerical computing, and careful technical testing.

• Develop and validate machine-learning models, training pipelines, and inference systems.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible workflows with Python and command-line tools.
• Optimize memory use and throughput, debug numerical or system-level failures, and verify technical results.
• Use coding agents in a coding-heavy workflow.

What it pays and takes

This is a fully remote, part-time contractor opportunity with flexible scheduling. The role is listed as entry level, while the work requires advanced academic or professional preparation in a quantitative field.

• Pay: $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Time: Approximately 15 hours per week, with flexible scheduling.
• Work arrangement: Fully remote contractor role.
• Location: Open to candidates in Algeria, Argentina, Austria, Bahrain, Bangladesh, Belgium, Brazil, Canada, Chile, Colombia, Denmark, Egypt, France, Germany, Ghana, Greece, India, Indonesia, Italy, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Lebanon, Malaysia, Mexico, Morocco, the Netherlands, Nigeria, Oman, Pakistan, Palestinian Territories, Peru, the Philippines, Portugal, Qatar, Saudi Arabia, Singapore, South Africa, Spain, Sri Lanka, Switzerland, Taiwan, Thailand, Tunisia, the United Arab Emirates, the United States, Uzbekistan, and Vietnam.
• Education: A master's degree or PhD in computer science, machine learning, artificial intelligence, applied mathematics, statistics, engineering, or a closely related quantitative discipline.
• Experience: Strong professional or research experience in machine learning and practical proficiency with Python.
• Useful background: Familiarity with PyTorch, JAX, NumPy, SciPy, SGLang, vLLM, llama.cpp, tokenizers, or transformers.
• Preferred experience: Work in a recognized technology, AI laboratory, research, or engineering environment. Exceptional open-source or academic experience may also qualify.

About AI training work

AI training work is the human side of building artificial intelligence. Specialists develop, test, and review the data, models, and systems that help AI produce more reliable results, so people with advanced technical experience can take on more demanding work.

Requirements

• Experience: Entry level