At a Glance
- Tasks: Manage and optimise the MLOps platform for seamless data product delivery.
- Company: Join a dynamic organisation focused on innovation and operational excellence.
- Benefits: Flexible working, generous leave, health insurance, and tailored benefits.
- Other info: Hybrid role with opportunities for professional growth and collaboration.
- Why this job: Lead cutting-edge ML operations and make a real impact in data science.
- Qualifications: Experience with data platforms and MLOps in complex environments.
The predicted salary is between 60000 - 80000 £ per year.
Type: Permanent – Hybrid working, averaging 2/3 days per month in the office.
Due to growth, we are hiring for two Platform Manager - ML Ops to join us permanently on a hybrid working basis, one working from the UK and the other in Kuala Lumpur, Malaysia. With this role, you will be accountable for the reliable, secure and efficient operation of the organisation’s MLOps platform and Machine Learning Operations (MLOps) capabilities. In this role you will report to the Head of Data Platform and Services. The role ensures platform services meet business needs, are well governed, and enable delivery teams to build, deploy and run data products and ML models at scale. This role is delivery-focused and works closely with data engineering, analytics, data science, information security and suppliers to embed platform standards, automate controls, and continuously improve stability, cost, and time‑to‑value. The Platform Manager drives operational excellence, balancing innovation with appropriate risk management and compliance for production data and AI services.
Key Responsibilities
- Own and manage the day-to-day operation of the Databricks Lakehouse Platform and MLOps services, ensuring high availability, performance, security, and user satisfaction.
- Lead platform service management activities, including incident, problem, change, and request processes, while coordinating support and escalation procedures.
- Develop and maintain standardized MLOps frameworks, tooling, and best practices to support the end-to-end machine learning lifecycle.
- Collaborate with Data Engineering and Data Science teams to operationalize ML models through CI/CD, automated testing, deployment, and monitoring capabilities.
- Ensure robust security, compliance, and governance controls across the platform, including access management, data protection, audit readiness, and risk mitigation.
- Own the Databricks platform roadmap, driving continuous improvement, technical standards, cost optimization, and scalable architecture patterns.
- Manage vendor and supplier relationships, overseeing service performance, support activities, release planning, and commercial considerations.
- Act as the primary platform stakeholder interface, providing guidance, training, documentation, and enablement to help teams effectively build and deploy data and AI solutions.
Qualifications and Experience
- Proven experience managing data/analytics platforms and/or MLOps capabilities in a complex enterprise environment.
- Hands‑on experience operating Databricks (workspace administration, cluster policies, jobs, Delta Lake, Unity Catalog, access controls, and production support).
- Experience implementing MLOps practices across the model lifecycle (CI/CD, versioning, monitoring, reproducibility).
- Strong stakeholder management; able to translate business outcomes into platform priorities and service commitments.
- Experience working with security, risk, and governance teams to evidence controls for data and AI services.
- Experience managing suppliers and delivery partners, including service performance and support processes.
Benefits (UK)
- A flexible working scheme
- 27 days annual leave
- Paid sick leave
- Bank holidays
- Health insurance
- Life insurance
- Pension plan with company contribution
- Car allowance (dependent on role)
- Income protection
- Paid maternity leave
- Paid paternity leave
- Paid parental leave
- Adoption leave
- Compassionate leave
- Paid bereavement leave
- Learning & development opportunities
- A wide range of flexible benefits that you can tailor to suit your lifestyle.
Benefits (Malaysia)
- A flexible working scheme
- 16 days annual leave
- Paid sick leave
- Bank holidays
- Group hospitalisation and surgical insurance
- Life insurance
- Transport allowance (dependent on role)
- Internet and/or phone allowance
- Paid maternity leave
- Paid paternity leave
- Paid marriage leave
- Paid bereavement leave
- Learning & development opportunities
- A wide range of flexible benefits that you can tailor to suit your lifestyle.
Visa Sponsorship: BSI is unable to provide visa sponsorship for this vacancy. BSI is an Equal Opportunity Employer dedicated to fostering a diverse and inclusive workplace.
Platform Manager: ML Ops & Data Platform Excellence employer: BSI
BSI is an excellent employer for those passionate about the medical devices sector, offering a dynamic and inclusive work environment that fosters creativity and excellence. With opportunities for professional growth and development, employees can thrive while delivering impactful training solutions that enhance client performance. The remote nature of this role allows for flexibility, making it an ideal position for those seeking meaningful and rewarding employment in a supportive setting.
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We think this is how you could land Platform Manager: ML Ops & Data Platform Excellence
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We think you need these skills to ace Platform Manager: ML Ops & Data Platform Excellence
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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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at BSI. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at BSI
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
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.
