AI Engineer

Jobtailor; Burgess Hill; On-site; GBP 30,000 - 52,000; Full time

Job summary

Jobtailor is seeking a graduate AI/ML Engineer to support development, testing, and integration of AI-driven solutions in a dynamic team in the UK. You will work on data retrieval pipelines, model training, evaluation, and deployment under guidance, collaborating with cross-functional partners.

The role emphasizes Python-based data processing, responsible AI practices, and participation in Agile ceremonies to deliver reliable AI-enabled features within project timelines.

Qualifications

• Bachelor’s or Master’s degree in a technical field (CS/ML/DS/AI/CE/SWE) before full-time start date.
• Graduation date between December 2026 and June 2027.
• Proficiency in Python and foundational data processing technologies.
• Foundational understanding of data structures, algorithms, OOP, debugging, testing, and problem solving.
• Understanding of supervised learning, unsupervised learning, model training, evaluation, feature engineering.
• Introductory understanding of LLM APIs, prompt-based interactions, retrieval patterns, or generative AI apps.
• Ability to support AI/ML development, testing, documentation, integration, or data pipelines under guidance.
• Awareness of responsible AI expectations, including reliability, safety, governance, privacy, compliance, and escalation.
• Strong communication, collaboration, documentation, and learning agility.

Responsibilities

• Support AI/ML model development, testing, and integration under guidance.
• Assist with data collection, preprocessing, transformation, and validation for training and evaluation.
• Debug and improve AI-enabled solutions for performance, reliability, explainability, maintainability, and quality.
• Support training workflows, inference endpoints, and prompt-based interactions.
• Collaborate with engineering, product, data, risk, security, and business partners to implement AI-driven solutions.
• Document model parameters, prompts, data pipelines, integrations, and decisions.
• Participate in Agile practices including sprint planning, stand-ups, demos, retrospectives, code reviews, and team ceremonies.
• Help ensure AI systems meet reliability, safety, governance, security, privacy, compliance, and escalation.

Skills

Python Programming

Data Processing

Problem Solving

Communication

Collaboration

Learning Agility

Education

Bachelor’s Degree

Master’s Degree

Tools

LLM APIs

NLP Techniques

ETL

Cloud Environments

Containerized Development

Model Deployment

CI/CD

Version Control

Job description

• Support development, testing, and integration of AI/ML models, LLM integrations, intelligent services, and data retrieval pipelines under guidance.
• Assist with data collection, preprocessing, transformation, and validation for model training, testing, evaluation, and implementation.
• Debug and improve AI-enabled solutions for performance, reliability, explainability, maintainability, and quality.
• Support model training workflows, inference endpoints, prompt-based interactions, evaluation routines, retrieval patterns, AI agents, and agentic workflows.
• Collaborate with engineering, product, data, risk, security, and business partners to implement AI-driven solutions.
• Document model parameters, prompts, assumptions, data pipelines, integrations, and technical decisions.
• Participate in Agile practices including sprint planning, stand-ups, demos, retrospectives, code reviews, and team ceremonies.
• Help ensure AI systems and features meet expectations for reliability, safety, governance, security, compliance, and escalation.

Requirements

• Must have earned a Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Computer Engineering, Software Engineering, or another technical field before the full-time start date.
• Students must have a graduation date between December 2026 and June 2027.
• Knowledge of Python and foundational data processing technologies.
• Foundational understanding of data structures, algorithms, object-oriented programming, debugging, testing, and problem solving.
• Foundational understanding of supervised learning, unsupervised learning, model training, evaluation, feature engineering, and experimentation.
• Introductory understanding of LLM APIs, prompt-based interactions, retrieval patterns, AI powered tools, or generative AI applications.
• Ability to support AI/ML development, testing, documentation, integration, or data pipeline activities under guidance.
• Awareness of responsible AI expectations, including reliability, safety, governance, security, privacy, compliance, and appropriate escalation.
• Strong communication, collaboration, documentation, and learning agility.
• Preferred: Experience through coursework, research, projects, open-source contributions, internships, hackathons, or extracurricular activities using Python, R, Java, JavaScript, or similar technologies.
• Preferred: Familiarity with NLP techniques and models including fuzzy matching, embeddings, BERT, transformers, and LLMs.
• Preferred: Exposure to LLM APIs, prompt engineering, prompt evaluation, tools, function calling, retrieval patterns, or agent workflow concepts.
• Preferred: Familiarity with APIs, data pipelines, ETL, cloud environments, containerized development, model deployment, or monitoring.
• Preferred: Awareness of CI/CD, version control, testing, code reviews, Agile development, and collaborative software engineering workflows.

Core Competencies

Demonstrates expertise in AI/ML model development, testing, and integration, with a strong foundation in Python and data processing technologies. Capable of collaborating across teams to implement AI-driven solutions while adhering to responsible AI practices and Agile methodologies.

Highest-signal resume keywords

• Python Programming
• AI/ML Model Development
• Data Pipeline Integration
• Agile Development Practices
• Responsible AI Awareness

Hard Skills

• Data Structures
• Algorithms
• Object-Oriented Programming
• Supervised Learning
• Unsupervised Learning
• Model Training
• Feature Engineering
• Debugging
• Testing
• Problem Solving

Soft Skills

• Communication
• Collaboration
• Documentation
• Learning Agility

Certifications & Qualifications

• Bachelor’s Degree
• Master’s Degree

Industry Keywords

• AI
• Machine Learning
• Data Science
• Artificial Intelligence
• Generative AI
• Agile Practices
• Data Retrieval Pipelines
• Prompt Engineering
• Fuzzy Matching
• Transformers

Tools & Technologies

• LLM APIs
• NLP Techniques
• ETL
• Cloud Environments
• Containerized Development
• Model Deployment
• CI/CD
• Version Control