Graduate Machine Learning Engineer - £30,000

JR United Kingdom; Kingston upon Hull; Hybrid; GBP 30,000 - 35,000; Full time

Job summary

A leading company seeks a Graduate Machine Learning Engineer in Kingston upon Hull. This role involves working on exciting AI and ML projects, with a mixture of in-office and remote work. Ideal candidates will possess a solid understanding of Python, SQL, and data analysis skills, contributing to innovative projects.

Qualifications

• Graduate role, preferably in Computer Science or related field.
• Passion for Artificial Intelligence and Machine Learning.
• Foundational knowledge in ML techniques.

Responsibilities

• Conduct exploratory data analysis to identify trends.
• Support implementation of AI/ML techniques across products.
• Create clear data-driven reports and visualizations.

Skills

Python

SQL

Data Analysis

Git

Machine Learning

Artificial Intelligence

Job description

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Graduate Machine Learning Engineer - £30,000, Kingston upon Hull, East Yorkshire

Client:

Location:

Kingston upon Hull, East Yorkshire, 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 a Graduate Machine Learning Engineer with a passion for Artificial Intelligence, Machine Learning, Mathematics, Data Analysis, Python, Git, SQL, and BI Tools. The role is based in Edinburgh, with a flexible working arrangement.

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.
• 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 to technical and non-technical audiences.
• Contributing to automation of data analysis workflows to streamline reporting and validation processes.