MLOps Engineer

Social network you want to login/join with:
London with relocation to Barcelona (Within the next 6-12 months)
Company:
Join a stealth start-up transforming how enterprises leverage their tabular data, unlocking unprecedented possibilities for analytics in major industries like finance, healthcare, and advertising. Their research team includes world-class AI experts from DeepMind who are rapidly growing and expanding our engineering team to push the boundaries of what's possible in tabular AI.
Responsibilities:
Develop and manage automated machine learning pipelines, CI/CD workflows, and orchestration frameworks for production-ready systems.
Design and implement robust model deployment using platforms like TorchServe, TensorFlow Serving, or Triton for reliable inference delivery.
Create low-latency, high-throughput inference systems with a focus on performance and scalability.
Implement seamless deployment processes with A/B testing, canary releases, and rollback mechanisms to ensure stability.
Set up logging, alerting, and monitoring to track model performance, reliability, and system health across environments.
Requirements:
Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
Proficient in Python (core skill), with strong experience in SQL
5+ years of experience as MLOps engineer or DevOps roles, working with MLOps platforms
Experience with Kubernetes on a major cloud provider and IAC
Please note that this role does not offer visa sponsorship
How to Apply:
Register your interest by sending your CV to Emily Burgess via the Apply link on this page.

#J-18808-Ljbffr