At a Glance
- Tasks: Build scalable MLOps infrastructure and transform research workflows into reliable systems.
- Company: Innovative biotechnology organisation focused on data and machine learning.
- Benefits: Competitive salary, bonus, equity, flexible remote work, and career growth opportunities.
- Other info: Collaborative environment with significant technical ownership and exposure to cutting-edge challenges.
- Why this job: Join a high-impact role shaping the future of machine learning and scientific computing.
- Qualifications: Strong experience in MLOps, Python, cloud platforms, and data engineering.
The predicted salary is between 90000 - 120000 £ per year.
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.
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.
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.
Senior MLOps & Data Engineer in Oxford employer: Proclinical
Proclinical is an exceptional employer dedicated to advancing healthcare through innovative project management. With a strong focus on employee growth, we offer opportunities for professional development and the chance to work on impactful projects within NHS settings across the UK and Ireland. Our collaborative work culture fosters open communication and teamwork, making it a rewarding environment for those looking to make a meaningful difference in the life sciences sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior MLOps & Data Engineer in Oxford
✨Get Involved in Local Research Communities
Tap into local biotechnology meetups and research forums. These are great places to mingle with industry professionals, share your passion, and even discover unadvertised job openings. It's all about getting your face known in the field!
✨Leverage University Alumni Networks
If you're a recent grad, don’t underestimate the power of your university’s alumni network! Reach out to alumni working in biotechnology to gather tips about job openings at companies like Proclinical. You'd be surprised how willing people are to help out a fellow grad!
✨Show Off Your Projects
Curate a portfolio showcasing any research projects or internships you've completed in biotechnology. This tangible evidence of your skills can really impress employers when you chat with them at networking events or interviews. It's about making that killer first impression!
✨Stay Up-to-Date with Industry Trends
Biotech is a fast-paced field, so keeping yourself updated with the latest advancements is crucial. Attend industry conferences, webinars, or workshops to broaden your knowledge and meet potential employers. Plus, it’ll give you fantastic talking points for your interviews at places like Proclinical!
We think you need these skills to ace Senior MLOps & Data Engineer in Oxford
Some tips for your application 🫡
Show Off Your Lab Skills:In the biotechnology field, it's super important to highlight your lab experience in your CV. Be sure to mention specific techniques or instruments you've mastered (think PCR, gel electrophoresis, etc.) and any relevant projects you've worked on. This will show Proclinical that you have the hands-on skills they need.
Tailor Your Technical Skills:Make sure to emphasise your technical skills, especially those relevant to the biotechnology sector. Include any software tools or programming languages you've used, like R or Python for data analysis, which could be key for this role at Proclinical.
Craft a Compelling Cover Letter:Since this is a full-time role, your cover letter should reflect not only your passion for biotechnology but also your long-term career ambitions. Share why you're excited about the work that Proclinical does and how you envision contributing to their goals. This shows that you’re not just looking for any job, but you're genuinely invested in this opportunity.
Include Your Papers and Projects:If you've published any papers or contributed to significant projects, mention them! These documents can boost your application and provide tangible evidence of your expertise in the biotechnology field. Don’t forget to link to any relevant publications or project summaries—this can set you apart from other candidates.
How to prepare for a job interview at Proclinical
✨Brush Up on Lab Techniques
Since you're eyeing a full-time gig in biotechnology, make sure you're well-versed in the lab techniques relevant to the role. Be ready to talk about PCR, CRISPR, or any specific methods mentioned in the job description at Proclinical. You might even be asked to demonstrate your understanding of these processes.
✨Know Your Bioinformatics Tools
Get comfortable with bioinformatics tools that are commonly used in the industry, like BLAST or Bioconductor. These are key in biotechnology, and having hands-on experience or at least familiarity can set you apart. Prepare to discuss any relevant projects you've worked on, especially if they involved data analysis or genomic research.
✨Show Your Teamwork Skills
Biotech often involves collaboration across multiple disciplines. Be ready to share stories that highlight your teamwork and communication skills, especially in research projects. Think about working with different teams at university or any internships – this is where you can show how well you fit into Proclinical's culture.
✨Research Recent Biotech Innovations
Stay updated on the latest trends and breakthroughs in biotechnology. Knowing what's happening in the field can help you engage in more meaningful discussions during your interview. Bring up recent articles or advancements that excite you, especially those related to the work being done at Proclinical. This shows your passion for the industry!
