Machine Learning Engineer, Entry

Paramount is on a mission to unleash the power of content and is seeking a Machine Learning Engineer to join their Applied Machine Learning Group. In this role, you will focus on enhancing the user experience by implementing features that optimize content recommendations and solve the 'Cold Start' problem for new users.

Responsibilities:

• Independent Delivery: Own the implementation of features for JBI (Jump Back In) and YNW (Your Next Watch)
• Retrieval Optimization: Use Qdrant to find high-relevance candidates for re-entry carousels based on session history and global trends
• Experiment Lifecycle: Use MLFlow to manage, track, and deploy experiments, ensuring a high bar for reproducibility
• Model Training: Develop and serve models in GCP using TensorFlow/PyTorch, incorporating Post-training RL for reward-based optimization
• Collaborative Quality: Participate in design reviews to ensure your components share the same high-reliability standards as the rest of the pod
• Solving Cold Start: Build the logic that makes the app feel personalized even for users we know very little about
• High-Commitment Accuracy: Optimize for the 'Play' button—the ultimate 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
• Background in multi-stage ranking or 'Cold Start' problems
• Experience with retrieval optimization and re-entry carousels
• Knowledge with Post-training RL for reward-based optimization