Proclinical Staffing
Senior MLOps & Data Engineer

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Senior MLOps & Data Engineer
Location: Oxford Based (Hybrid)
Type: Permanent
Salary: £90,000 - £120,000 + Bonus + Equity + Benefits
The Opportunity
We're supporting an innovative biotechnology organisation that is investing heavily in the next generation of data, machine learning and scientific computing capabilities.
As part of a growing technology team, you will play a key role in building the infrastructure that enables scientists, engineers and researchers to develop, deploy and scale machine learning solutions within a highly data-driven environment.
This is a hands-on position suited to an experienced engineer who enjoys solving complex technical challenges across cloud infrastructure, data platforms, workflow automation and machine learning operations. You will help transform research and analytical workflows into reliable, secure and scalable production systems.
Responsibilities
- Design and build scalable MLOps infrastructure to support model deployment, monitoring, retraining and lifecycle management.
- Productionise machine learning and scientific computing workflows using Python, container technologies and modern software engineering practices.
- Develop cloud-native data pipelines across AWS and GCP to support ingestion, transformation, storage and inference workloads.
- Build integrations between laboratory systems, operational platforms and cloud environments using APIs and event-driven architectures.
- Support the collection, processing and management of large-scale experimental and operational datasets.
- Establish best practices for model versioning, experiment tracking, reproducibility, observability and platform governance.
- Collaborate with scientific, engineering and operational teams to convert research code into reliable internal products and services.
- Contribute to the design of AI-driven workflow orchestration and intelligent automation solutions.
- Improve platform reliability, security, scalability and cost efficiency.
- Create and maintain technical documentation, standards and operational runbooks.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Required Experience
- Strong commercial experience in MLOps, machine learning platform engineering, data engineering or cloud infrastructure engineering.
- Advanced Python development experience within production environments.
- Strong experience with Docker, Kubernetes and CI/CD pipelines.
- Experience building and operating cloud-native platforms in AWS and/or GCP.
- Experience designing and supporting data pipelines within complex technical environments.
- Familiarity with workflow orchestration tools such as Airflow, Prefect or Dagster.
- Experience implementing monitoring, logging, observability and platform governance practices.
- Strong understanding of software engineering principles, testing and deployment best practices.
- Ability to work collaboratively with technical and non-technical stakeholders.
Desirable Experience
- Experience within life sciences, healthcare, biotechnology, research, scientific computing or regulated environments.
- Familiarity with laboratory information systems, data platforms or scientific software ecosystems.
- Exposure to AI agents, workflow automation frameworks or advanced machine learning operations.
- Experience supporting GPU-based workloads and large-scale model execution environments.
- Knowledge of compliance, auditability or data integrity requirements within highly regulated industries.


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What's on Offer
- Opportunity to help shape the architecture of a growing machine learning and data platform.
- High-impact role with significant technical ownership.
- Exposure to cloud infrastructure, machine learning, automation and scientific computing challenges.
- Flexible remote working environment.
- Long-term career growth within a rapidly evolving technology organisation.
If you are having difficulty in applying or if you have any questions, please contact Neil Walton @ n.walton@proclinical.com
Apply Now
If you are interested in applying to this exciting opportunity, then please click 'Apply' or to speak to one of our specialists please request a call back at the top of this page.
Proclinical is a leading life sciences recruiter focused on finding exceptional people and matching them with the finest positions across the globe. Proclinical is acting as an Employment Agency in relation to this vacancy.
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