Senior AI Engineer - LLMs and Finetuning

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 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 Senior AI Engineer 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:

• Design and build generative AI applications tailored to complex financial and legal workflows, leveraging state-of-the-art models to deliver innovative, practical solutions that streamline decision-making and unlock new efficiencies.

• Drive end to end model development lifecycle, leading the team in best practices, ensuring reproducible research and well managed model delivery/deployment.

• Collaborate cross functionally to share diverse ideas, understand business problems, and elevate/mentor your teammates.

• Translate complex problems into well-defined scoped bets in an internal startup style environment, dynamic and fast-paced.

• Learn and apply ground-breaking research and approaches in advanced topics, iterating improvements with a fail fast mentality.

• Be a proactive sharer of compelling ideas/work to the rest of the team and organisation. We want you to help lead/push the adoption of AI throughout 9fin.

This role is focused on improving the models themselves. While experience with retrieval systems, knowledge graphs, and AI applications is valuable, the core challenge is building proprietary financial-domain models that outperform general-purpose LLMs on the workflows that matter most to 9fin users.

This role will be a great fit if you:

• Open-Weight LLMs
  :
  Deep experience evaluating, adapting, and deploying open-weight models such as Llama, Qwen, Mistral, and Gemma for production use cases.

• Fine-Tuning & Post-Training
  :
  Expertise in supervised fine-tuning, preference optimisation, instruction tuning, and domain adaptation to improve model performance on specialised tasks.

• Training Data & Synthetic Data Generation
  :
  Strong experience building high-quality datasets, generating synthetic training data, and creating data flywheels that continuously improve model quality.

• Model Evaluation
  :
  Ability to design rigorous benchmarks, evaluation frameworks, and regression testing systems that measure real-world model performance.

• Financial Domain Modelling
  :
  Experience applying AI to complex financial and legal domains, including credit, restructuring, debt instruments, filings, court documents, and capital markets workflows.

• Training Infrastructure
  :
  Familiarity with distributed training, parameter-efficient fine-tuning, GPU optimisation, inference acceleration, and cost-performance trade-offs.

• Model Optimisation
  :
  Experience with distillation, quantisation, and other techniques for improving model quality, latency, and operating costs.

• Production ML Engineering
  :
  Ability to build and operate training pipelines, deployment systems, evaluation infrastructure, and model monitoring in production…