At a Glance
- Tasks: Build and optimise machine learning systems for our Disputes platform at scale.
- Company: Join a dynamic tech company focused on innovation and collaboration.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Enjoy a startup-like environment with excellent career advancement potential.
- Why this job: Make a real impact by turning raw data into production-ready features.
- Qualifications: 5+ years in MLOps/ML Engineering with strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
How you’ll make an impact:
- Build systems for training, deploying and monitoring machine learning models used in our Disputes platform, at scale.
- Build and optimize data pipelines and backend services to process dispute and payment data in real time.
- Build and scale our feature store for use-cases both online and offline.
- Take complete ownership of delivering comprehensive, end-to-end features within a startup-like setting, driving the entire lifecycle from requirement refinement, data pipeline construction and model training to troubleshooting and production deployment.
- Turn raw data into production-ready features that feed our dispute systems.
- Collaborate with platform and backend engineers to integrate models seamlessly.
Experience and qualifications:
- 5+ years of experience as MLOps / ML Engineer.
- High proficiency in writing clear, production-ready Python code.
- Experience with production ML models (online or offline) and standard MLOps practices.
- Experience with monitoring and observability of production systems, with a strong sense of ownership.
- Experience with training and operating models on Databricks.
- Familiarity in Cloud-based application development (we use AWS).
We think you need these skills to ace Senior Machine Learning Engineer
Machine Learning Engineering
MLOps
Python Programming
Data Pipeline Construction
Feature Store Development
Model Training
Production Deployment
