Lead MLOps Engineer – Hybrid, Scale ML Platforms & Telematics

Hastings Direct; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Car allowance

27 days annual leave + bank holidays

Private medical insurance (PMI)

Pension contribution match up to 10%

Cycle to work

Job summary

Hastings Direct is seeking a Lead MLOps Engineer to design, build and maintain the infrastructure for the full ML lifecycle. You will ensure predictive models and data products are reliable, scalable, and deliver measurable business value.

The role sits in the Telematics Data Value team, collaborating with data scientists, data engineers, and engineers. You will lead automation, feature generation, model training, deployment and monitoring while advancing cloud-native approaches and governance

Qualifications

• Strong Python skills and experience building and operating machine learning solutions in cloud environments.
• Experience with MLOps tooling and practices, including CI/CD, containerisation, orchestration, model deployment, monitoring, and infrastructure automation.
• Experience using SQL and working with large-scale data platforms.
• Familiarity with modern cloud platforms such as Azure, AWS, or GCP.
• Experience collaborating across teams of Data Scientists, Data Engineers, Software Engineers, Operational and Commercial stakeholders.
• Understanding of software engineering best practices including testing, version control, code review, and observability.

Responsibilities

• Provide technical leadership on ML platform architecture, helping shape the tooling, standards, and operating model used to deliver machine learning across the organisation.
• Develop and maintain automated workflows for feature engineering, model training, testing, deployment, monitoring, and retraining.
• Partner with Data Scientists and Data Engineers, and ML Engineers to operationalise predictive models and data products.
• Establish best practices for ML observability, model performance monitoring, CI/CD, versioning, governance, and reproducibility.
• Improve the reliability, scalability, and efficiency of our machine learning and data platforms.
• Work with cloud-native technologies and infrastructure-as-code to support modern ML workloads.
• Present technical solutions and outcomes to engineering, operational, and commercial stakeholders.
• Evaluate emerging technologies and contribute to the team's engineering standards and best practices.

Skills

Python

MLOps tooling

CI/CD

Containerisation

Orchestration

Model deployment

Monitoring

Infrastructure automation

SQL

Cloud platforms

Tools

Docker

Kubernetes

Job description

Hastings Direct is seeking a Lead MLOps Engineer to design, build and maintain the infrastructure for the full ML lifecycle. You will ensure predictive models and data products are reliable, scalable, and deliver measurable business value.

The role sits in the Telematics Data Value team, collaborating with data scientists, data engineers, and engineers. You will lead automation, feature generation, model training, deployment and monitoring while advancing cloud-native approaches and governance