Level

9fin

Applied AI Manager

AI in this role

ml-opscomputer-visionnlp

About 9fin

9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion.

Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value workflows across global markets.

Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in-class retention driven by deep workflow adoption.

We’re at a defining inflection point. With proven product-market fit and strong, global market pull, 9fin is accelerating toward becoming the category-defining platform for debt markets worldwide.

The Opportunity

The Data Science team is growing at 9fin! We are doing world-class work with groundbreaking technologies to build data-driven products using machine learning, computer vision, natural language processing, speech and audio, and knowledge/data mining. We are looking for a Applied AI Manager to accelerate our application of AI across teams and products. Come and join us, you will get to build large-scale AI powered systems, learn and apply the latest techniques, and work alongside other great researchers and engineers!

Every day is different, but here's an example of the kind of things you'll work on:

  • Lead the design and delivery of complex ML and GenAI systems, ensuring solutions are robust, scalable, and aligned with business goals.

  • Guide the team in end-to-end model development - from experimentation and evaluation through deployment and monitoring - with a focus on reproducibility and reliability.

  • Drive architectural decisions for data-intensive, AI-driven applications, making informed trade-offs between cutting-edge approaches and practical production readiness.

  • Mentor and grow engineers across levels, sharing best practices in software engineering, ML/AI, and cloud infrastructure.

  • Collaborate cross-functionally with stakeholders across the company to shape roadmaps, scope ambitious projects, and balance technical innovation with delivery.

  • Champion engineering excellence - from coding standards and CI/CD pipelines to observability and incident management - creating a culture of technical rigor and continuous improvement.

  • Be a visible technical leader within 9fin, pushing forward the adoption of AI/ML across teams and influencing company-wide strategy.

About You

This role will be a great fit if you:

  • Have proven experience leading engineering teams in a high-growth, fast-paced environment.

  • Care deeply about people development - mentoring engineers, conducting thoughtful performance reviews, and building inclusive, high-performing teams.

  • Combine strong software engineering skills (Python preferred) with deep knowledge of AI/ML frameworks, GenAI tooling, and modern data/infra stacks.

  • Have hands-on experience building and deploying ML/GenAI systems in production, ideally in domains with high complexity (finance, legal, or similar data-heavy spaces).

  • Lead architectural discussions and technical trade-offs while staying close enough to dive into details when needed.

  • Know your way around cloud infrastructure (AWS preferred) and modern MLOps practices.

  • Thrive in a collaborative, startup-style environment: adaptable, decisive, and excited to work cross-functionally to deliver real business impact.

Benefits

We’re a scaling start up, and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people. We also offer huge amounts of responsibility, an abundance of opportunity for growth and a platform to truly excel.

Financial & Insurance

  • Competitive Salary (our salary bands are benchmarked at the top end of the market)

  • Equity

  • Pension (your minimum contributions are 4% with 9fin matching up to 7%)

  • Private Medical Insurance

  • Paid sick leave with Income Protection for long periods of illness

  • Group Life Assurance

  • Season Ticket Loan & Cycle to Work schemes

Time off

  • 25 holiday days per year

  • Local public holidays (with the ability to exchange them for alternative days)

  • Hybrid working model, to allow you the flexibility to decide how, where and when you do your best work

  • Work abroad for up to 3 months a year

  • 1 month paid sabbatical after 5 years of service

  • Enhanced parental leave & flexible working arrangements available

Training & Culture

  • Professional learning and development budget

  • AI experimentation budget

  • Quarterly team socials

  • Summer and Winter company social events

9fin is an equal opportunities employer

At 9fin we are dedicated to building and promoting a fair and inclusive workplace where everyone can reach their full potential and truly belong. We recognize that building diverse teams enables a more creative and productive environment. If you’re excited about this role but your experience doesn’t perfectly align with the job description, we encourage you to apply anyway. You might just be who we’re looking for — either for this role, or perhaps another.

How we rate this

Applied AI Manager at 9fin rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsComputer VisionNLP

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  3. What NLP problem have you worked on, and how did you measure whether it actually worked?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: ML Ops, Computer Vision, and NLP. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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