MLOps Engineer

London (Hybrid) | £75,000 to £85,000 + Bonus + Benefits

Are you a hands-on MLOps Engineer who enjoys building scalable platforms rather than simply maintaining them? This is a chance to take ownership of the infrastructure behind a growing AI and machine learning environment, helping shape the future of production ML systems while working closely with data scientists and machine learning engineers.

The Company

They are a specialist AI and data consultancy that develops machine learning, predictive analytics and NLP solutions for a diverse client base. As their platform and client demand continue to grow, they are investing heavily in the infrastructure, tooling and processes that support production AI services. You'll join a collaborative technical team where you'll have genuine influence over architectural decisions and platform direction.

The Role

You will play a key role in building and scaling the infrastructure that underpins production AI and machine learning solutions.

Responsibilities include:

• Developing and maintaining scalable MLOps infrastructure
• Owning orchestration platforms such as Dagster, Airflow or Prefect
• Working directly with Python applications and services
• Managing Kubernetes-based production environments
• Improving monitoring, observability and platform reliability
• Implementing infrastructure as code using Terraform or Bicep
• Enhancing CI/CD processes and deployment automation
• Partnering with data scientists and ML engineers to support production workloads

Your Skills & Experience

• Strong commercial experience working in MLOps environments
• Excellent Python software engineering skills
• Hands-on experience with Dagster, Airflow, Prefect or similar orchestration tools
• Experience with monitoring, observability and deployment tooling
• Infrastructure as code expertise, ideally Terraform or Bicep
• Understanding of production machine learning, predictive analytics or NLP systems
• Azure cloud technologies
• LLM infrastructure

What They Offer

• Up to 10% bonus
• Hybrid working with 1 to 2 days per week in the London office
• Private healthcare and additional benefits
• Six-monthly reviews and progression opportunities
• High levels of ownership and technical autonomy
• The opportunity to help build the next generation of AI infrastructure