← Back to AI Training Jobs

AI training & evaluation

ML Engineer

micro1

We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization…

Compensation
Per accepted task

Track this job

My Jobs
  • ai-machine-learning
  • Technical
  • AI training & evaluation
Hours
15 hours per week

Employer description and requirements

ML Engineer

Pay: $80–$150/hour

Location: Global, fully remote

Job Type: Contractor (~15 hours per week)

Schedule: Flexible—you choose the hours and days you work, including weekends if desired

We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python.

The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements.

This is a very coding heavy role. Candidates but have experience using coding agents with python in their workflow.

What You’ll Work On

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 programmatic workflows using Python and command-line tools.

Required Qualifications

A 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 with Python and coding agents.

Relevant tools may include:

PyTorch

JAX

NumPy and SciPy

SGLang

vLLM

llama.cpp

Hugging Face Transformers

Hugging Face Tokenizers

Equivalent tools may also be considered when the candidate demonstrates directly relevant depth.

Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred. Exceptional open-source or academic experience may also qualify.

Process

Apply to the role and complete the screening questions.

Complete an AI interview of approximately 30 minutes.

Complete the hiring manager review.

Compensation Structure

Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.

Minimum submission requirements apply.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

Application screening questions

What is your expected hourly rate in USD?

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

If moving forward, would you be able to review and sign the contract within 24 hours, and begin tasking within 24-48 hours of receiving your credentials?

Do you have a portfolio or any open source evidence of your work you'd like to share with us?

Do you have teaching/instructor experience? If so, what does it look like? (Not a deal breaker)

What does your experience with Python look like?

Please select the tools you have experience with: (Would highly recommend making it visible on your application)

Please describe your experience with the previously selected tools.

Other published fields (read alongside the description):

Published hourly-rate fields: {'max': 150, 'min': 80}

Source page's structured applicant-location list: Bangladesh, Hong Kong, India, Indonesia, Japan, Kazakhstan, Kyrgyzstan, Malaysia, Pakistan, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, Uzbekistan, Vietnam, Austria, Belarus, Belgium, Denmark, France, Germany, Greece, Italy, Netherlands, Portugal, Russia, Spain, Switzerland, United Kingdom, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Algeria, Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Tunisia, United Arab Emirates, United States, Canada, Nigeria, Kenya, South Africa, Ghana, Ethiopia