DSR Global
MLOps AI Lead & Databricks Platform Specialist

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MLOps AI Lead & Databricks Platform Specialist
We are currently seeking an MLOps AI Lead & Databricks Platform Specialist to join a global end client, taking ownership of the Databricks platform and supporting the delivery of robust, scalable MLOps capabilities.
We are ideally looking for someone on a permanent basis, although contract-to-permanent could also be considered.
Location: Hybrid – 2 -3 days per week onsite in London, Covent Garden / Milton Keynes.
Experience Required:
- 3 – 5 years’ 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.
- Heavy on Databricks
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.
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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.
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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.
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.


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