Graduate Machine Learning Engineer - £30,000

JR United Kingdom; Stoke-on-Trent; Hybrid; GBP 30,000; Full time

Job summary

A leading AI company is seeking a Graduate Machine Learning Engineer in Stoke-on-Trent, offering an entry-level salary of £30,000. This role involves applying machine learning techniques to support product developments while gaining experience in a collaborative environment that encourages innovation. Candidates should have a strong foundation in AI and data analysis, along with skills in Python, SQL, and machine learning principles.

Qualifications

• Passionate and enthusiastic about Machine Learning and AI.
• Foundational knowledge of diverse machine learning techniques.
• Experience with data analysis and visualization.

Responsibilities

• Implement cutting-edge AI/ML techniques across multiple product lines.
• 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, Stoke-on-Trent

Client:

Location: Stoke-on-Trent, 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 to join an exciting AI company in Edinburgh.

Responsibilities include:

• Possessing foundational knowledge of diverse machine learning techniques suitable for various 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 Proof of Concept projects by analyzing data outputs and assessing model performance.
• Creating clear reports and visualizations to communicate findings.
• Contributing to automation of data analysis workflows.