At a Glance
- Tasks: Design and maintain MLOps pipelines for AI models, ensuring smooth deployment and monitoring.
- Company: Innovative R&D team in East Molesey, focused on AI and machine learning.
- Benefits: Competitive salary, career growth, and the chance to work with cutting-edge technology.
- Other info: Join a dynamic team driving automation and innovation in a scientific environment.
- Why this job: Make a real impact by bridging machine learning engineering with applied data science.
- Qualifications: Experience in MLOps, strong Python skills, and familiarity with ML libraries required.
The predicted salary is between 34000 - 69000 £ per year.
Salary: £34,000 - 69,000 per year
Requirements:
- MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience
- Proven experience designing and deploying MLOps pipelines, including MLflow, Azure ML, Azure DevOps, or similar tools
- Strong programming skills in Python and familiarity with common ML/AI libraries, including Scikit-learn, TensorFlow, and Keras
- Experience implementing machine learning and large language models, including deployment, monitoring, and retraining
- Familiarity with software engineering guidelines, including version control, Git, CI/CD, containerisation, Docker, and workflow orchestration
- Knowledge of cloud platforms and scalable compute environments, with Azure preferred
- Understanding of data governance, model documentation, and reproducibility in a regulated or research-heavy context
- Ability to align machine learning initiatives with business objectives in a scientific or regulated environment
Responsibilities:
- Design, build, and maintain resilient Machine Learning Operations pipelines that support the complete lifecycle of AI models, from creation to implementation and supervision
- Ensure the successful deployment of machine learning and large language models in practical operational settings, transforming research findings into functional business tools
- Support the development and evaluation of ML models, including both standard machine learning and neural network-focused models, as requested by R&D teams
- Develop standardised, reusable workflows that can be applied across different projects and scientific areas
- Collaborate with scientists and engineers to incorporate AI solutions into daily R&D tasks
- Implement tools for version control, testing, and continuous integration to ensure quality, security, and traceability of AI solutions
- Develop automated reporting systems that make results from AI models easier to interpret, share, and act on
Technologies: AI, Azure, CI/CD, Cloud, DevOps, Docker, Git, Support, Keras, Machine Learning, Network, Python, Security, TensorFlow
We are a full-time R&D-focused team based in East Molesey, England, United Kingdom, seeking an experienced Senior MLOps Engineer to bridge machine learning engineering with applied data science. We work closely with scientific and operational teams to improve the robustness, scalability, and reliability of AI tools, while driving automation and standardisation across the ML lifecycle to enable faster, data-informed decision-making and innovation. This role offers the opportunity to contribute significantly to the development, deployment, and advancement of machine learning and AI systems in a scientific and regulated environment.
Senior MLOps Engineer employer: Sivara GmbH
As a Senior MLOps Engineer at our R&D-focused team in East Molesey, you will thrive in a collaborative and innovative work culture that prioritises employee growth and development. We offer competitive salaries, comprehensive benefits, and the unique opportunity to work at the forefront of AI technology, transforming scientific research into impactful business solutions while fostering a supportive environment for continuous learning and professional advancement.
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We think this is how you could land Senior MLOps Engineer
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We think you need these skills to ace Senior MLOps Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
