Applied Scientists — Machine Learning (MSc. or PhD)

micro1; United States; Remote; USD 83,000 - 165,000; Full time

Job summary

micro1 is a data lab that helps AI labs and enterprises train foundational models and agents. We provide frontier evaluations, RL environments, and contextual evaluations to monitor and improve AI agents in enterprise settings.

Applied Scientists — Machine Learning (Contractor) work involves model development, training and inference systems, debugging and optimization, with flexible hours and remote global availability.

Qualifications

• Master's degree or PhD in CS/ML or related quantitative field.
• Strong ML experience.
• Proficiency with Python and coding agents.

Responsibilities

• Develop and validate ML models, training pipelines, inference systems.
• Build reproducible ML workflows using Python and command-line tools.
• Optimize memory and throughput, debug numerical or system-level issues.

Skills

Machine Learning

Python

Coding agents

Education

Master's degree in Computer Science or ML

PhD in CS/ML

Job description

pay

Required Skills
Machine Learning
About micro1
micro1 is a data lab that helps AI labs & Enterprises train foundational models and agents. We provide frontier evaluations and reinforcement learning environments to improve LLM capabilities, as well as contextual evaluations to monitor and improve AI agents in enterprise settings.

Our AI recruiting agent sources and vets domain experts for our data platform that enables rapid production of high-quality training data. Our research spans high-value, specialized domains (legal, medical, finance, coding, etc.), where expert-level data is the hardest to produce and most valuable for advanced model performance. Our pipeline performance system ensures both quality and velocity.

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.


• 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.

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

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.

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