Job Title: Python (Django) Engineer
Location: Remote with 1 day per week office-based working
Reporting to: Lead Engineer
Contract type: Permanent
Working pattern: 37.5 hours p/w
Salary: Up to £45,000 per annum + pension + benefits
About TalentMapper
TalentMapper is an AI-powered talent intelligence platform helping mid-to-large enterprises solve their biggest workforce challenges: skills gaps, internal mobility, and retention. We replace static spreadsheets with a dynamic, "skills-first" engine that uses machine learning to map career paths and match employees to opportunities.
It's personal for us – most of our team have faced and overcome barriers (such as social mobility) in organisations, based on our backgrounds and we are determined to create change, helping those in our reach to achieve their potential. We provide an end-to-end solution for managing talent. We are specialists in all things talent management and we know that talent technology in the workplace is the key to creating highly successful organisations.
Our Mission
TalentMapper was founded with a mission to improve talent management, removing traditional barriers to career growth and development and unleash the potential of all people in the workplace, so they can achieve extraordinary results.
Job Purpose
We need a hands-on Backend Engineer who loves building robust features and solving complex data problems. You will work directly on our "career pathing" algorithms and data ingestion pipelines. This role is perfect for someone who is strong in Python and wants to get closer to Machine Learning and Data Engineering without necessarily being a full-time Data Scientist.
Values Profile
All team members must have a personal commitment to unleashing potential in our society by aligning their behaviours to our values:
* Be innovative – seek and welcome new approaches to everyday tasks and behaviours.
* Be inclusive – understand, respect, and respond to the intersectional needs of our team and our clients.
* Challenge the status quo – question and evaluate existing structures and processes.
* Remove barriers – focus on efficiency and performance by eradicating bias and exclusive processes.
Here's what you'll do:
* Feature Development: Develop and maintain core backend features for the TalentMapper platform using Python and Django.
* Data Engineering: Optimise data ingestion pipelines that process thousands of CVs and skills profiles to power our platform.
* Algorithm Support: Help rebuild and train our core skills-matching algorithms alongside our senior technical leaders.
* Write Quality Code: Ensure all contributions are clean, maintainable, and supported by high unit test coverage.
* Performance Tuning: Proactively debug production issues and optimise SQL query performance for faster data retrieval.
* AI Integration: Effectively integrate backend logic with AI/ML models (e.g., HuggingFace) to enhance our "skills-first" engine.
Experience Required
* Python & Django: Proven professional experience shipping production-ready backend code.
* Algorithmic Thinking: Strong understanding of data structures and efficient logic implementation.
* Coding Standards: Solid understanding of SOLID principles and the importance of writing maintainable code.
* Containerisation: Comfortable working with Docker in a local development environment.
* Version Control: Solid knowledge of Git and collaborative development workflows.
Skills Required
* Problem Solving: A natural ability to diagnose complex technical challenges and propose effective solutions.
* Technical Agility: Ability to work at the intersection of traditional application development and data processing.
* Pragmatism: An understanding of how to balance high-quality code with the speed required in a growing startup.
* Communication: Ability to collaborate effectively within a small, agile engineering squad.
Beneficial Skills (Nice-to-Haves)
* Data Science Tools: Familiarity with Pandas and/or ETL pipelines.
* AI/ML Interest: Exposure to HuggingFace, PyTorch, or Natural Language Processing (NLP).
* Modern Infrastructure: Understanding of CI/CD pipelines (GitHub Actions or Cloud Build).
* Modern Databases: Exposure to NoSQL (MongoDB) or Graph databases (Neo4j).