Bloomreach is building the world’s premier agentic platform for personalization.We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey.
We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses.
We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey.
We're designing the future of autonomous marketing, taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do.
And we're building all of that on the intelligence of a single AI engine — Loomi AI — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora.
Bloomreach is seeking a seasoned Senior Machine Learning Engineer to own the design and implementation of cutting-edge AI and GenAI driven algorithmic components for search, recommendation and behavioral insights that are used to personalize digital experiences for our customers. The salary starts at €4,800 gross per month, along with restricted stock units and other benefits. We are currently allowing flexibility for our employees to work from anywhere for the respective region (Central & Eastern Europe) or we are happy to meet you in our offices in Bratislava (Slovakia) or Brno, Prague (Czechia) on a full-time basis.
Your Responsibilities:
Design, develop, and enhance ML/AI models which mainly power Search and Recommendation.
Process historical data, search queries, product cathalog, and images to extract hidden relations and features.
Conduct research to explore ongoing cutting-edge ML techniques (especially deep learning) and conduct a quick POC.
Work closely with Data Engineers and Senior Data Scientists to integrate and scale ML components to a production-level that can handle terabytes of data.
Continuously learn and stay up to date with the current state-of-the-art techniques by reading research papers and attending AI/ML conferences.