The company

Unitary’s purpose is to make the internet safer to improve lives and create a fairer world. We are a rapidly growing start-up developing best-in-class AI models that automatically detect and classify harmful content online. Our AI combines the strengths of human moderation (accurate video classification) with the benefits of automated detection (speed and scalability). This cutting-edge technology will help us solve real-world problems in content moderation and beyond. We believe in an online world free from harm, where we can trust AI to make safe and fair decisions.

We have raised about $25M in VC funding from top-tier funds, including Creandum and Plural, and operate at a significant scale - analysing millions of images and videos daily from the world’s largest platforms. But we are just at the beginning of our journey - and we are very excited about our plans for growth over the coming year and beyond!

The role

We are now looking for a senior Machine Learning Operations Engineer to help build our new Machine Learning Platform to keep up with the best-in-class models in our field. Your deep knowledge in ML Operations will be crucial in transforming our approach to machine learning and advancing our technological capabilities.

Your mission will be to ensure all Unitary’s models are working at their maximum performance by creating the architectures our data scientists need to productionise our models. You will run and monitor our machine learning models as they come to market, initially through hands-on support and gradually through self-service tooling for them to deliver value autonomously.

As part of this role, you will:

• Design, develop and operate a new ML Data platform that addresses current limitations and scales with our product strategy
• Define and manage tables and transformations in Delta Lake to support data and ML pipelines
• Design, implement, and optimise APIs for ML model deployment
• Collaborate with ML Engineers and product teams to integrate machine learning models into production environments
• Ensure AI services' reliability, observability, availability, and performance
• Make key decisions on how we implement machine learning and computer vision, shaping the future of Unitary