Machine Learning Engineer

Who are we?

Gain.pro is on a mission to provide global private market visibility. Our industry-leading platform combines advanced AI tech with local-for-local research. It delivers the highest quality information on the companies that matter to you most.

We serve 100% of MBB/Big-4 advisories, clients representing >$500bn of private equity capital and more than 70% of the top-20 global M&A houses. Examples include Blackstone, Goldman Sachs and McKinsey. We lead the market on customer satisfaction, as validated by external research (User Evidence survey 2023).

Gain.pro has been named as one of Europe’s top 50 fastest growing businesses, operating globally with offices in Amsterdam, London, Frankfurt, Warsaw and Bangalore.

The role

As a Machine Learning Engineer, you will be pivotal in our R&D efforts. Your focus will be on developing in-house ML models that extract private market insights and refining validation strategies for various use cases—primarily NLP—leveraging third-party APIs. Collaborating closely with backend and data engineers, you will integrate these models into production systems while continuously monitoring performance, identifying anomalies, and iteratively enhancing model robustness for significant business impact. This role requires a strong foundation in applied ML, rigorous experimentation, and a pragmatic approach to bridging R&D with production.

Our data

At Gain.pro, we track every company in the world with >10 employees - amounting to millions of companies globally. Data for large companies is curated by our in-house research team (200 FTEs, and counting), while data for smaller companies is processed entirely automatically - by ingesting and processing thousands of publications on a daily basis.

Our team

Our engineering team is based in Amsterdam, where most of us typically work 2 days a week onsite. We are a lean team of 14 senior engineers (backend & frontend, data, DevOps, ML) and 5 colleagues in product and design. Together, we operate efficiently and pragmatically, and everyone’s voice is heard. We are rapidly scaling, so as an early joiner of our ML team, there is plenty of room to have a big impact and set directions. Apart from a short daily stand-up, we keep meetings to a minimum (think max 1-2 per week). We do a monthly team event on Tuesday evenings that you are welcome to join.