Senior Machine Learning Engineer

About the role

You will be the first Senior Engineer in Machine Learning at Primer, working side‑by‑side with the Staff Engineer to build the ML function from the ground up. You’ll partner with product, data and engineering teams to identify high‑impact use cases and help shape the technical direction as the function evolves.

Key responsibilities

• Own the full lifecycle of ML‑powered features – from research and testing to training, deployment and production monitoring.
• Productionise smart routing decisions across the payment flow, building versioned, CI/CD‑enabled, observable ML infrastructure.
• Collaborate with product, data and engineering to turn promising use cases into shipped, measured outcomes.
• Adopt an impact‑first mindset for experimentation and model evaluation, favouring pragmatic solutions.
• Mentor other engineers on ML techniques and trade‑off decisions.
• Engage directly with customers to validate ideas and test against real usage.
• Help set technical direction and prioritise use cases within the emerging ML team.
• Establish reliable, repeatable ML patterns and practices built on solid foundations.

Required profile

• Senior experience in ML engineering, data science or applied research with production deployments (API, batch or streaming).
• Strong statistical mindset; able to design and interpret experiments and A/B tests.
• Solid software‑engineering background, familiar with modern infrastructure, data tooling and MLOps challenges.
• Understanding of reinforcement‑learning concepts (e.g., multi‑armed or contextual bandits).
• Cloud experience – AWS preferred, GCP or Azure also acceptable.
• Comfortable working in ambiguous, fast‑moving environments and defining processes as you go.

Required skills

• Python
• scikit‑learn
• XGBoost
• TensorFlow
• PyTorch
• Keras
• AWS
• GCP
• Azure

What we offer

• Fully remote, globally distributed work environment.
• Competitive share options.
• Uncapped holiday with a minimum of 25 days.
• Co‑working space access in major cities.
• Workations and annual company retreat.
• Best‑in‑class equipment and £500 home‑office stipend.
• Generous learning budget and private medical insurance.