Staff AI/ML Engineer (MLOps) — Fintech Platform

Checkout.com; Greater London; Hybrid; GBP 110,000 - 170,000; Full time

Benefits offered by this job

Hybrid Working Model

Office snacks

Job summary

Checkout.com is seeking a Staff Level AI / ML engineer to accelerate adoption of AI across the platform. You’ll lead MLOps from vector databases to model serving within the data and AI platform, collaborating with cross‑functional teams.

You will prototype, evaluate and implement AI solutions, ensure scalable and secure deployments, and help shape AI governance in a fast‑paced, global environment with hybrid office days.

Qualifications

• Proficiency in Python and AI toolkits.
• Experience with PyTorch, Pandas, Hugging Face Transformers.
• Solid engineering skills, including designing and implementing services / data models and features.
• Expertise with cloud platforms and containerisation (Docker/Kubernetes).
• Experience with modern data platforms and data processing workflows.
• Familiarity with hosted AI platforms (Bedrock, Sagemaker, VertexAI).
• Strong communication and cross-team collaboration.

Responsibilities

• Collaborate with teams to research, scope, and validate AI use cases that drive business value.
• Drive AI adoption by combining rigorous evaluation with operational maturity for high-value applications.
• Design, refine and build MLOps components of the data and AI platform across the stack.
• Implement CI/CD pipelines and ensure best practices for model deployment, security, and compliance.
• Work as part of our AI/ML guild to drive new approaches and use cases.
• Monitor and optimise system performance for scalability, security, and efficiency.

Skills

Python proficiency

Communication

Problem solving

Teamwork

Adaptability

Tools

PyTorch

Pandas

Hugging Face Transformers

Docker

Kubernetes

AWS

GCP

Azure

BigQuery

Databricks

Bedrock

SageMaker

VertexAI

Job description

Checkout.com is seeking a Staff Level AI / ML engineer to accelerate adoption of AI across the platform. You’ll lead MLOps from vector databases to model serving within the data and AI platform, collaborating with cross‑functional teams.

You will prototype, evaluate and implement AI solutions, ensure scalable and secure deployments, and help shape AI governance in a fast‑paced, global environment with hybrid office days.