Junior Gen AI Engineer

eTeam; Manchester; On-site; GBP 57,000 - 75,000; Full time

Job summary

eTeam is recruiting for a role in Manchester focused on building machine learning models using both structured and unstructured data. The position emphasizes synthetic data creation, GenAI-driven rule extraction, and governance-aligned production solutions.

You will work with AI engineers to integrate models into MVPs and establish robust evaluation frameworks. The role requires strong Python and SQL skills, experience with POC development, and the ability to define statistical metrics for ML

Qualifications

• Design and develop machine learning models using structured and unstructured data.
• Generate synthetic datasets for testing, training, and validation.
• Apply GenAI to extract, interpret, and translate policy documents into structured rules.
• Proficient in Python and SQL for data analysis, data manipulation, and scalable solutions.
• Collaborate with AI engineers and solution architects to integrate ML components into MVPs.
• Experience building POCs and implementing guardrails with statistical metrics.

Responsibilities

• Design and implement ML models for predictive analytics.
• Generate and curate synthetic datasets for testing and validation.
• Define governance standards and evaluation metrics for GenAI systems.
• Collaborate with solution architects to deliver end-to-end MVPs.

Skills

Python

SQL

Machine Learning

GenAI

Job description

We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.

Location: Manchester

Work setup: 4 days onsite/week

Pay Rate: £358 per day all inc. (PAYE through Umbrella)

Role Description:

• Design and develop machine learning models using structured and unstructured data, supporting predictive analytics, classification, and optimization use cases.
• Generate synthetic datasets from sample or limited data, ensuring data quality, coverage, and usability for testing, model training, and validation (including creation of “golden datasets”).
• Apply Generative AI techniques to extract, interpret, and translate policy documents into structured rules, workflows, or decision logic.
• Proficient in Python and SQL for data analysis, data manipulation, and enabling scalable data-driven solutions in production environments.
• Collaborate with AI engineers and solution architects to integrate ML and GenAI components into end-to-end MVPs, ensuring alignment with business requirements and governance standards.
• Experience building POCs and implementing guardrails, including defining and applying statistical metrics for ML model validation and evaluation frameworks for generative AI systems.

Please note that candidates are often shortlisted within 48 hours.