Junior AI Engineer
Location: Guildford (3 days per week in office, rest remote)
Salary: £40,000 – £60,000 DOE
We are looking for a Masters-level Junior AI Engineer to join a team at the forefront of Artificial Intelligence and Applied Machine Learning. This role is ideal for someone with a strong academic foundation who is eager to apply their skills to real-world challenges, working at the intersection of data science, symbolic reasoning, and modern machine learning.
You’ll play a key role in developing intelligent workflows, experimenting with emerging technologies, and contributing to innovative AI research while receiving guidance and support to grow into a specialist role.
Key Responsibilities
- Develop and improve AI workflows, including data preprocessing, rule generation, and interpretability pipelines.
- Work with diverse datasets (CSV, Excel, JSON, XML), applying encoding, imputation, and feature engineering techniques.
- Explore integrations between symbolic AI approaches and large language models (LLMs).
- Contribute to the design of end-to-end AI/ML pipelines, ensuring scalability and reproducibility.
- Support database and systems development for efficient knowledge discovery.
- Collaborate with colleagues to ensure research and development efforts translate into real-world applications.
- Produce clear documentation and share knowledge across the team.
Required Skills & Experience
- A Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related discipline.
- Strong proficiency in Python and common data science libraries (e.g., Pandas, NumPy, scikit-learn).
- Solid understanding of data preprocessing, feature engineering, and pipeline automation.
- Familiarity with relational databases and schema design.
- Excellent research and problem-solving skills, with the ability to experiment and test new approaches.
- Strong communication skills and experience with collaborative tools (e.g., Git workflows).
Desirable Skills
- Exposure to inductive logic programming, symbolic AI, or hybrid ML-symbolic methods.
- Familiarity with cloud platforms (AWS, GCP, Azure) or containerisation (Docker).
- Knowledge of knowledge graphs or rule-based reasoning frameworks.
- Interest in applying AI to domains such as healthcare, finance, or customer behaviour.
This is a fantastic opportunity for a motivated Masters graduate who wants to make an impact in applied AI, while developing expertise in both symbolic reasoning and machine learning within a collaborative, forward-thinking environment.
