Graduate Machine Learning Engineer - £30,000

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

Job summary

A leading AI company is seeking passionate Graduate Machine Learning Engineers for office-based roles in Edinburgh with one day of remote work. Successful candidates will support various AI/ML techniques, conduct data analyses, and contribute to automating workflows. Start date expected between July and August.

Qualifications

• Candidates should possess foundational knowledge across various machine learning techniques.
• Passion and enthusiasm for AI and ML are essential.

Responsibilities

• Support the implementation of cutting-edge AI/ML techniques.
• Conduct exploratory data analysis to identify trends and anomalies.
• Assist in analyzing data outputs and assessing model performance.

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, Slough

Client:

Location: Slough, United Kingdom

Job Category: Other

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.

Paying up to £30,000 basic

IMPORTANT PLEASE READ - Aiming for candidates to have a START DATE between July & August

We are seeking passionate & enthusiastic Graduate Machine Learning Engineers 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 candidates to start between the end of June and end of August.

Responsibilities include:

• Possessing foundational knowledge across various machine learning techniques suitable for different data types.
• Supporting the implementation of cutting-edge AI/ML techniques across multiple product lines.
• Conducting exploratory data analysis to identify trends and anomalies.
• Assisting in PoC projects by analyzing data outputs and assessing model performance.
• Creating clear reports and visualizations to communicate findings.
• Contributing to automation of data analysis workflows.