micro1
micro1Verified listing
RemoteHot

Machine Learning Researcher (MSc. or PhD)

60–120/hr
Remote
Posted October 24, 2026
contract
100 openings
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Listing checked October 24, 2026 · pay as published by micro1

Overview

micro1 seeks Machine Learning Researchers with an MSc or PhD to join an AI training project. The work centers on model development, training and inference systems, numerical computing, and performance optimization in Python. This is a coding-heavy contractor role, about 15 hours per week, with a flexible schedule you set yourself. Pay ranges from $60 to $120 per hour, and tasks are paid per completed output that meets project specs.

What You'll Do8

  • 1Create and validate machine learning models, training pipelines, and inference systems.
  • 2Implement model components, data pipelines, evaluation systems, and numerical methods.
  • 3Build reproducible programmatic workflows using Python and command-line tools.
  • 4Solve challenging machine-learning engineering tasks that involve model modification or implementation.
  • 5Construct reproducible training or inference workflows that meet correctness and performance requirements.
  • 6Optimize memory usage or throughput in model implementations.
  • 7Debug numerical or system-level failures and verify that implementations satisfy objective criteria.
  • 8Review and validate machine-learning tasks submitted by others.

Requirements8

  • 1Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative field.
  • 2Strong professional or research experience in machine learning.
  • 3Practical proficiency with Python and coding agents.
  • 4Experience at a well-established technology company, AI laboratory, research organization, or similar engineering environment is strongly preferred.
  • 5Exceptional open-source or academic experience may also qualify.
  • 6Equivalent tools may be considered when the candidate shows directly relevant depth.
  • 7Ability to work independently on coding-heavy tasks with minimal supervision.
  • 8Comfort with command-line tools and reproducible workflow design.

Who Should Apply

This role suits a researcher or engineer with an MSc or PhD and a strong machine learning background, who writes Python daily and uses coding agents in their workflow. You should be comfortable with numerical computing, performance tuning, and debugging system-level issues. Experience at a recognized tech company, AI lab, or research organization is a plus.

Salary Insight

The rate is $60 to $120 per hour. Compensation is output-based: you are paid per task that meets the project specifications, and the time each task takes varies with your experience and workflow. Minimum submission requirements apply.

Pay and demand for Machine Learning & AI roles

Aggregated

Typical pay

$70/hour

This role

$60–$120/hr

Most Machine Learning & AI roles pay $42–$96 per hour. This role's pay falls inside that range.

Based on 1,070 similar roles that publish pay · 302 publish only a top rate; those count at the rate they gave

Typical rangeMedian payThis role

Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.

Live similar roles
1,206
Listed in last 30 days
648
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98%

Hiring most right now: micro1 (357) · SME Careers (253) · Mercor (160)

Most requested skills · share of roles

  • ai evaluation
    13%
  • ai training
    13%
  • llm evaluation
    12%
  • data annotation
    10%

Figures from Machine Learning & AI roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.

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Location

TypeRemote
LocationRemote
This is a remote position

Compensation

$60–120/hr

Required Skills

Machine Learning

Application Tip

When you apply, highlight specific Python projects where you used coding agents, and quantify results such as memory reduction or throughput gains. Mention any experience at a well-known tech company, AI lab, or research organization, and be ready to discuss numerical debugging and reproducible workflow design in the AI interview.

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