Partnered with a global insurance company who specialise in providing market leading and innovative cover for household pets, having achieved remarkable growth and now operating as a Billion Dollar organisation they are scaling their Data Engineering and Analytics practise and keen to bring onboard an experienced MLOps Engineer to spearhead the deployment of AI and Machine Learning models and ensure best practises are adhered across the business.
Scope of role:
- Design, build and deploy AI/Machine Learning systems in production.
- Develop scalable AI/ML Solutions with a focus on model implementation, performance and reliability.
- Take ownership of the End to End AI/ML pipelines through deployment and monitoring.
- Contribute to their evolving MLOps Strategy, including model monitoring, retraining pipelines and enabling best practises.
- Implement and evaluate new tools, frameworks to improve end to end AI/ML lifecycle from concept to production.
- Collaborate extensively with Product Managers, Engineers and Data Engineers supporting the integration of models and ensuring robust data pipelines.
Experience required:
- Experience designing, building and deploying AI / Machine Learning workflows on Google Cloud Platform, in particular Vertex AI.
- Architecting and maintaining CI/CD pipelines that deliver models into production.
- Cloud infrastructure and IAC experience, with Terraform supporting scalable ML systems.
- Strong knowledge of Data Governance, Data lineage and security practises.
- Agile/Kanban setup in a fast-paced scale-up environment.
- Cloud-based GPU model training and online/offline feature stores.
- Full-Stack Data Science background from training and deploying AI/ML models.
If this opportunity aligns with your background and career aspirations please share your details to daniel.neaves@harveynash.com , your latest CV and availability for a call.
