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Who are we?

Gain.pro is on a mission to serve everyone who wants to find, understand and track the companies that matter to them. Our platform empowers investors, advisors, and C-suite executives with the deepest private market insights, combining human curation with GenAI for faster, data-driven decisions.

We serve 100% of MBB/Big-Four advisories, clients representing over $1 trillion of private capital and more than 70% of the top-20 global M&A houses – including blue chip firms such as Blackstone, Goldman Sachs and McKinsey. With an NPS of >80, we lead the market on customer satisfaction and strive for excellence in everything we do.

Operating globally with offices in Amsterdam, London, Frankfurt, Warsaw, Bangalore and (soon) New York, Gain.pro is one of Europe’s fastest growing businesses, recognized in the Deloitte Technology Fast 500 EMEA 2023 and the 8th edition of FT1000: Europe’s Fastest Growing Companies.

The role

As Python Engineer, your role will focus on developing the backbone of our AI platform, which enhances the data curation pipelines of our research teams and delivers deep company insights to our users. You will work on expanding and optimizing the platform's APIs, collaborating with our AI researchers to deploy AI models and integrate them with our web app (Golang service). Your technical expertise will shape the platform's architecture and ensure it scales reliably with the organization.

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 (300 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 15 Senior Engineers (Back-End & Front-End, Data, DevOps, ML) and 6 colleagues in Product and Design. Together we operate in an efficient and pragmatic way, where 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 (max. 1-2 per week).