Graduate Machine Learning Engineer - £30,000 (Edinburgh)

ZipRecruiter; City of Edinburgh; On-site; GBP 25,000 - 30,000; Full time

Job summary

A leading AI company in Edinburgh is seeking Graduate Machine Learning Engineers. This role offers a blend of office and remote work, with a focus on implementing AI/ML techniques and conducting data analysis. Ideal candidates should be passionate about AI and proficient in relevant tools.

Qualifications

• Foundational knowledge of machine learning techniques.
• Proficient in Python, Git, SQL, and BI Tools.

Responsibilities

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

Skills

Artificial Intelligence

Machine Learning

Mathematics

Data Analysis

Python

Git

SQL

BI Tools

Education

Graduate

Job description

Job Description

Edinburgh office 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 start between the end of May and August

We are seeking Graduate Machine Learning Engineers to join 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 is available for start dates between late June and August.

Responsibilities:

1. Possess foundational knowledge across a diverse range of machine learning techniques suitable for various data shapes and types.
2. Support the implementation and application of cutting-edge AI/ML techniques across multiple product lines, aiming to contribute effectively to product enhancement.
3. Conduct exploratory data analysis to identify trends, patterns, and anomalies in datasets.
4. Assist in the preparation and execution of Proof of Concept (PoC) projects by analysing data outputs and assessing model performance.
5. Create clear, data-driven reports and visualisations to communicate findings from AI/ML models to technical and non-technical audiences.
6. Contribute to automation of data analysis workflows to streamline reporting and validation processes.