- 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.
Join our Artificial Intelligence team as a Senior Software Engineer (with an overlap into ML Engineer) and help us revolutionize marketing with ML-powered solutions! You'll work on cutting-edge technologies, impacting millions of users, and contributing to a product that truly makes a difference. Working in one of our Central European offices (Bratislava, Brno, Prague) or from home on a full-time basis, you´ll become a core part of the Engineering Team.
What challenge awaits you?
You'll face the exciting challenge of building and maintaining ML-powered features in a production environment, ensuring they are reliable, scalable, and deliver real value to our users. You'll work alongside a team to overcome the unique challenges of building and running ML models in a SaaS environment, including managing data complexity, optimizing for performance, and ensuring model robustness.
You will cooperate with your teammates, Data Science engineers, and Engineering and Product leaders to speed up ML-powered features' delivery (from ideation to production) by applying principles of continuous discovery, integration, testing, and other techniques from Agile, DevOps, and MLOps mindsets. This will involve building efficient workflows, automating processes, and fostering a culture of collaboration and innovation.
Your job will be to:
a. Design & Deliver new features
- Translate business requirements for ML-powered features into technical specifications and design documents.
- Collaborate with data scientists to ensure new ML features' technical feasibility and scalability.
- Define and develop back-office API endpoints (to configure the features) as well as the high-performance serving endpoints.
- Develop and implement ML models, algorithms, and data pipelines to support new features.
- Deploy and monitor new features in prod
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