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Graduate Machine Learning Engineer - £30,000

JR United Kingdom

Basingstoke

Hybrid

GBP 30,000

Full time

7 days ago
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Job summary

A leading AI company is seeking Graduate Machine Learning Engineers for their Edinburgh office, offering a competitive salary of up to £30,000. The role includes a combination of office and remote work, focusing on machine learning techniques, data analysis, and contributing to innovative AI projects.

Qualifications

  • Passionate about AI and Machine Learning.
  • Foundational knowledge of machine learning techniques.
  • Proficient in Python, Git, SQL, and BI Tools.

Responsibilities

  • Conduct exploratory data analysis to identify trends and anomalies.
  • Support the implementation of advanced AI/ML techniques.
  • Assist in Proof of Concept projects.

Skills

Machine Learning
Python
Data Analysis
SQL
Git
BI Tools

Education

Graduate degree

Job description

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EU work permit required:

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Job Views:

2

Posted:

10.06.2025

Expiry Date:

25.07.2025

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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 Graduate Machine Learning Engineers for an exciting AI company in Edinburgh. The role is suitable for candidates passionate about Artificial Intelligence, Machine Learning, Mathematics, Data Analysis, and proficient in Python, Git, SQL, and BI Tools. The position offers a salary of up to £30,000 and involves a mix of office and remote work.

Responsibilities include:

  • Having foundational knowledge of various machine learning techniques suitable for different data types.
  • Supporting the implementation of advanced 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 models.
  • Creating reports and visualizations to communicate findings effectively.
  • Contributing to automation of data analysis workflows.
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