Graduate Machine Learning Engineer

Nichols Digital Ltd; City of Edinburgh; Hybrid; GBP 25,000 - 30,000; Full time

Job summary

A leading AI company in Edinburgh is seeking Graduate Machine Learning Engineers to start between late June and August. Candidates should have a passion for Artificial Intelligence, solid knowledge in machine learning techniques, and proficiency in Python, Git, and SQL. This role will involve implementing AI techniques and conducting extensive data analysis.

Qualifications

• Foundational knowledge in machine learning techniques.
• Proficient in Python and Git.
• Passion for AI and data analysis.

Responsibilities

• Implement cutting-edge AI/ML techniques for product enhancement.
• Conduct exploratory data analysis to identify trends.
• Contribute to automation of data analysis workflows.

Skills

Artificial Intelligence

Machine Learning

Mathematics

Data Analysis

Python

Git

SQL

BI Tools

Education

Bachelor's degree in relevant field

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 looking for Graduate Machine Learning Engineers with a passion for Artificial Intelligence, Machine Learning, Mathematics, Data Analysis, and proficiency in Python, Git, SQL, BI Tools.

An exciting AI company in Edinburgh is seeking several passionate & enthusiastic Graduate Machine Learning Engineers to start between the end of June and the end of 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.