Applied Scientists — Machine Learning (MSc. or PhD)
micro1Legit · not rated yetPosted 3 days ago
Pay: $60–120/hr
- Who can apply
- Countries not stated in the listing
- Hours
- 15 hrs/week · Freelance
- Where
- Remote, work from home
- Job type
- Expert (SME) review
- Openings
- 100 openings
At a glance: A freelance, remote expert (SME) review job with micro1. It pays $60–120/hr for 15 hours a week. The listing doesn't say which countries can apply.
Countries not stated
The posting doesn't say which countries can apply, so check before you apply. What micro1 says in general: Recruits worldwide apart from residents of 21 countries and regions, among them China, Russia, Ukraine, Iran, Venezuela and Ethiopia; some listings accept applicants from the US, UK or Canada only
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What happens after you click Apply
- You leave AI Trainer HQ and go to micro1’s own site.
- Pick a role, apply and answer the screening questions attached to it
- Sit the AI interview with Zara, spoken and recorded, about 20–40 minutes
- Complete a technical assessment if the role has one, then a hiring-manager review
- Take the offer, sign your Deel contract and clear the KYC identity check
How this pay compares
This job pays more than 80% of the 204 other science (PhD) jobs on the board that state pay; 15% pay more.
- This job
- $90/hrMiddle of $60–120/hr
- Median on micro1
- $65/hrFrom 287 other paid jobs
- Median in science (PhD)
- $65/hrFrom 204 other paid jobs
Requirements
- Qualifications
- Machine Learning
- Languages
- English
- Equipment
- Computer with a reliable internet connection
About this job
Applied Scientists — Machine Learning (MSc. or PhD)
Pay: $60–$120/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.
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.
Listing history
- First seen on our board
- (2 days ago)
- Posted by micro1
- (3 days ago)
- Last checked
- Source
- micro1
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