Über
Own the implementation of features for JBI (Jump Back In) and YNW (Your Next Watch) Use Qdrant to find high-relevance candidates for re-entry carousels based on session history and global trends Use MLFlow to manage, track, and deploy experiments Develop and serve models in GCP using TensorFlow/PyTorch Participate in design reviews Build the logic that makes the app feel personalized for users with little data Optimize for the "Play" button as a signal of user commitment Requirements:
3+ years in MLE Experience with GCP and MLFlow Proficiency in TensorFlow/PyTorch Knowledge with Vector DBs Proven ability to implement features that solve the "Cold Start" problem for new users Experience managing, tracking, and deploying experiments to ensure a high bar for reproducibility. Benefits:
medical dental vision 401(k) plan life insurance coverage disability benefits tuition assistance program PTO
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.