Senior MLOps & Data Engineer — Cloud AI Platforms

Proclinical Staffing; Oxford; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Proclinical Staffing in Oxford is seeking a Senior MLOps & Data Engineer for a permanent hybrid role. You will design and implement scalable MLOps infrastructure to support model deployment, monitoring and lifecycle management across AWS/GCP.

You will productionise ML workflows in Python, build data pipelines, integrate lab systems and ensure observability, governance and cost efficiency for a data-driven biotech environment.

Qualifications

• Strong commercial experience in MLOps, machine learning platform engineering or cloud infrastructure engineering.
• Advanced Python development experience in production environments.
• Experience with Docker, Kubernetes and CI/CD pipelines.
• Experience building and operating cloud-native platforms in AWS and/or GCP.
• Experience designing data pipelines in complex environments.
• Familiarity with workflow orchestration tools (Airflow, Prefect or Dagster).
• Experience with monitoring, logging, observability and governance practices.
• Strong software engineering principles and deployment practices.
• Ability to work with technical and non-technical stakeholders.
• Experience in life sciences, biotechnology or regulated environments.
• Exposure to AI agents or workflow automation frameworks.
• Experience supporting GPU-based workloads.

Responsibilities

• Design and build scalable MLOps infrastructure to support model deployment, monitoring and lifecycle management.
• Productionise ML workflows using Python, container technologies and modern software practices.
• Develop cloud-native data pipelines across AWS and GCP for ingestion, transformation, storage and inference.
• Build integrations between lab systems, operational platforms and cloud environments via APIs and event-driven architectures.
• Support collection and processing of large-scale experimental and operational datasets.
• Establish best practices for model versioning, experiment tracking and governance.
• Collaborate with scientific, engineering and operational teams to convert research code into internal products.
• Contribute to AI-driven workflow orchestration and automation solutions.
• Improve platform reliability, security, scalability and cost efficiency.
• Create and maintain technical documentation and runbooks.

Skills

MLOps

Python

Docker

Kubernetes

CI/CD

AWS/GCP

Data pipelines

Observability

Collaboration

GPU workloads

Tools

Airflow

Dagster

Prefect

Job description

Proclinical Staffing in Oxford is seeking a Senior MLOps & Data Engineer for a permanent hybrid role. You will design and implement scalable MLOps infrastructure to support model deployment, monitoring and lifecycle management across AWS/GCP.

You will productionise ML workflows in Python, build data pipelines, integrate lab systems and ensure observability, governance and cost efficiency for a data-driven biotech environment.