Applied AI Researcher

We're building cutting-edge LLM-powered tools that supercharge investment research for the world's most demanding deal teams. Our clients include several of the top 10 global private equity firms, Big 4 professional services firms, and leading consulting practices: organisations responsible for deploying billions of dollars annually.

We're a profitable, bootstrapped company with a growing team of ~28 people based in London and New York. We 10x'd our revenue in 2025 and are on track to grow 2-3x again this year. Junior saves clients an average of 10 hours per week, and we're expanding fast into new verticals including investment banking, hedge funds, and research firms.

As our founding NLP/ML hire, you'll have the unique opportunity to:

• Translate product and business needs into applied ML/NLP solutions, coming up with novel research synthesis ideas and proving their business value through rapid prototyping.

• Develop and optimize retrieval, search, and ranking algorithms by combining semantic embeddings, behavioral signals, and structured database queries. Build custom reranking models.

• Fine-tune SLMs/LLMs for high-accuracy, low-latency tasks such as classification, query rewriting, summarization, and personalization.

• Apply advanced alignment and reliability techniques (e.g., DPO, fine-tuning strategies, evaluation-driven iteration) to improve user experience and trust.

• Experiment with summarization and synthesis methods to transform large sets of unstructured interview notes into structured insights.

• Contribute to product decisions, direction and prioritization

• Shape our engineering culture

We’re live with >20 enterprise clients, and already have 10s of thousands of calls on our platform. There’s lots of data to improve on and build.

We're looking for product-minded ML engineers who:

• Based in NYC

• Experienced NLP/ML researcher with strong knowledge of RAG, LLMs, and Generative AI pipelines.

• Experience with

• Proven experience building production ML systems, including search, information retrieval, and structured outputs

• Have strong communication skills and a desire for a client-facing role

• Are able to break down AI/ML problems for a non-technical audience clearly and succinctly, and translate their suggestions into testable experiments.

• Have a strong bias to action, highly organised and experienced working with senior stakeholders to deliver large projects end to end

• Excited to build a team

All the usual benefits (competitive pay and equity, private healthcare etc). Unusual benefits:

• Gym membership

• In-office cook

• Summers working in Greece by the beach