Graduate Machine Learning Engineer - £30,000

JR United Kingdom; Chester; Hybrid; GBP 30,000; Full time

Job summary

A leading AI company in Edinburgh seeks Graduate Machine Learning Engineers for a role starting between July and August. Candidates will work one day a week remotely, contributing to innovative projects while gaining experience in machine learning and data analysis within a supportive environment.

Qualifications

• Foundational knowledge across diverse machine learning techniques.
• Skills in Python, data analysis, and AI.
• Ability to create reports and visualizations.

Responsibilities

• Support implementation of AI/ML techniques to enhance products.
• Conduct exploratory data analysis to identify trends and patterns.
• Assist in the preparation of Proof of Concept (PoC) projects.

Skills

Artificial Intelligence

Machine Learning

Mathematics

Data Analysis

Python

Git

SQL

BI Tools

Job description

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Graduate Machine Learning Engineer - £30,000, Chester

Client:

Location:

Chester, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

Job Views:

2

Posted:

10.06.2025

Expiry Date:

25.07.2025

Job Description:

Edinburgh based role, with one day a week remote/home working and the rest in the office.

Salary up to £30,000 basic

IMPORTANT: Candidates should aim for a start date between July & August.

The role is for a Graduate Machine Learning Engineer with skills in Artificial Intelligence, Machine Learning, Mathematics, Data Analysis, Python, Git, SQL, and BI Tools.

An exciting AI company in Edinburgh is looking for several passionate & enthusiastic Graduate Machine Learning Engineers to start between the end of June and the end of August.

Responsibilities include:

• Possessing foundational knowledge across a diverse range of machine learning techniques suitable for various data shapes and types.
• Supporting the implementation and application of cutting-edge AI/ML techniques across multiple product lines to enhance products.
• Conducting exploratory data analysis to identify trends, patterns, and anomalies.
• Assisting in the preparation and execution of Proof of Concept (PoC) projects by analyzing data outputs and assessing model performance.
• Creating clear, data-driven reports and visualizations to communicate findings effectively to technical and non-technical audiences.
• Contributing to automation of data analysis workflows to streamline reporting and validation processes.