Machine Learning Engineer

Data Freelance Hub; Remote; GBP 125,000 - GBP 150,000; Part time

Job summary

A freelance data platform is seeking a Machine Learning Engineer for a short-term, project-based role. This remote opportunity offers $100 to $120 per hour and requires strong experience in machine learning engineering and applied ML research. Responsibilities include designing evaluation suites, assessing AI solutions, and translating ML workflows into structured benchmarks. Candidates should possess excellent communication skills and an ability to work independently to meet tight deadlines.

Qualifications

• Strong experience in machine learning engineering or applied ML research.
• Hands-on experience with model development, experimentation, and evaluation.
• Background in ML research in industry or academic settings preferred.

Responsibilities

• Design and write detailed evaluation suites for machine learning engineering tasks.
• Assess AI generated solutions across model training, debugging, optimization, and experimentation.
• Translate real world ML workflows into structured benchmarks for frontier models.
• Apply strong technical judgment to evaluate ML system design choices and tradeoffs.
• Work independently within a research driven, asynchronous project environment.

Skills

Machine learning engineering

Applied ML research

Model development

Experimentation

Technical communication

Job description

Overview

This role is for a Machine Learning Engineer on a short-term, project-based hourly contract, offering $100 to $120 per hour. Key requirements include strong experience in machine learning engineering and applied ML research, with a preference for industry or academic backgrounds.

Location: Remote, United Kingdom | Currency: $ USD

Commitment: Short-term, project-based

Date: February 8, 2026

Responsibilities

• Design and write detailed evaluation suites for machine learning engineering tasks.
• Assess AI generated solutions across model training, debugging, optimization, and experimentation.
• Translate real world ML workflows into structured benchmarks for frontier models.
• Apply strong technical judgment to evaluate ML system design choices and tradeoffs.
• Work independently within a research driven, asynchronous project environment.

Qualifications

• Strong experience in machine learning engineering or applied ML research.
• Hands on experience with model development, experimentation, and evaluation.
• Background in ML research in industry or academic settings preferred.
• Strong written communication skills and high attention to technical detail.
• Ability to work independently and deliver high quality outputs on short timelines.

Application Process

• Upload resume
• Short assessment
• Submit form

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