Applied AI Manager: Lead GenAI & ML at Scale (Hybrid)

9fin

Greater London

Hybrid

GBP 90.000 - 135.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Benefits dieser Stelle

Equity
Pension (your minimum contributions) 4
Private Medical Insurance
Paid sick leave with Income Protection
Group Life Assurance
Season Ticket Loan
Cycle to Work

Zusammenfassung

9fin in London is expanding its Data Science team and seeking an Applied AI Manager to accelerate the application of AI across products. You will build large-scale AI-powered systems, leverage cutting-edge techniques, and work with researchers and engineers.

You'll mentor engineers, guide end-to-end model development, and drive architectural decisions for data-heavy applications while balancing production readiness and business goals.

Qualifikationen

  • Proven experience leading eng teams in high-growth env.
  • Experience building and deploying ML/GenAI systems in production.
  • Strong software engineering in Python and ML tooling.
  • Comfort with cloud infra and MLOps practices.

Aufgaben

  • Lead design and delivery of complex ML/GenAI systems.
  • Guide end-to-end model development from experimentation to deployment.
  • Drive architectural decisions for data-intensive AI apps.
  • Mentor engineers across levels in ML/AI and cloud infra.
  • Collaborate with stakeholders to shape roadmaps and balance innovation with delivery.
  • Champion engineering excellence including CI/CD and observability.

Kenntnisse

Python
AI/ML frameworks
GenAI tooling
Cloud infrastructure
MLOps

Tools

AWS

Jobbeschreibung

9fin in London is expanding its Data Science team and seeking an Applied AI Manager to accelerate the application of AI across products. You will build large-scale AI-powered systems, leverage cutting-edge techniques, and work with researchers and engineers.

You'll mentor engineers, guide end-to-end model development, and drive architectural decisions for data-heavy applications while balancing production readiness and business goals.

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