Applied Scientist II - Recommendation Systems

Overview

Applied Scientist II to design, build, and deploy large-scale recommendation systems and ML/GenAI-driven features for Glance’s personalized experiences.

What you'll do

• Design and develop large-scale recommendation systems with advanced ML and ranking approaches.
• Build and operate ML models for personalization, prediction, and content understanding on high-volume data.
• Create rapid experimentation workflows to validate hypotheses and measure business impact.
• Own data preparation, model training, evaluation, and deployment pipelines with engineering counterparts.
• Monitor model performance, detect drift/failure modes, and identify improvement opportunities.
• Collaborate with Design, UX Research, Product, and Software Engineering to integrate ML/GenAI features.
• Work with stakeholders to align ML initiatives with strategic priorities.

What you'll need

• 3+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
• Deep expertise in ML and recommendation systems (e.g., collaborative filtering, ranking models, content-based approaches, embeddings).
• Experience with deploying ML workflows/models in production systems.
• Big data processing experience (e.g., Spark, distributed data systems) and cloud computing.
• Ability to design end-to-end ML solutions from prototype to production.
• Proficiency in Python and comfort with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
• Strong experience with big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).

Details

• Location: Bangalore.