ML Engineer

RemoteJobsOne; Greater London; Remote; GBP 83,000 - 156,000; Full time

Job summary

RemoteJobsOne is seeking an experienced ML Engineer for a fully remote, contractor role (approximately 15 hours/week) open to UK-based candidates. You will work on cutting-edge ML tasks, from model development to inference systems, with Python as a core tool.

The role is highly coding-intensive and requires a master's or PhD in a quantitative field, strong ML experience, and proficiency with Python and coding agents. Flexible scheduling is offered.

Qualifications

• A master's degree or PhD in Computer Science, ML, AI, 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.

Responsibilities

• 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.

Skills

Python

Coding agents

Machine Learning

Education

Master's degree or PhD in a relevant field

Tools

PyTorch

JAX

NumPy

SciPy

SGLang

vLLM

llama.cpp

Hugging Face Transformers

Hugging Face Tokenizers

Job description

IMPORTANT: after you apply, please check your email. We send you a link to complete your application — it is not considered until that last step is done. If you do not see it, check your spam folder.

This is a fully remote position, open to candidates based in United Kingdom.

Pay: $80–$150/hr

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

1. Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
2. Implement model components, data pipelines, evaluation systems, and numerical methods.
3. Build reproducible programmatic workflows using Python and command-line tools.

Required Qualifications

1. A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
2. Strong professional or research experience in machine learning.
3. Practical proficiency with Python and coding agents.

Relevant tools may include:

1. PyTorch
2. JAX
3. NumPy and SciPy
4. SGLang
5. vLLM
6. llama.cpp
7. Hugging Face Transformers
8. 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

1. Apply to the role and complete the screening questions.
2. Complete an AI interview of approximately 30 minutes.
3. 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

1. 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.