Staff Applied Scientist- Recommendation Systems

Overview

Staff Applied Scientist focused on building and running large-scale recommendation and personalization ML systems for Glance products.

What you'll do

• Design, build, and deploy large-scale recommendation and personalization models using high-volume data.
• Drive rapid experimentation from hypothesis to offline evaluation and online A/B testing.
• Develop and productionize end-to-end ML pipelines across data prep, feature engineering, training, evaluation, and monitoring.
• Partner with Product, Engineering, Design, UX, and Business to deliver scalable ML solutions.
• Monitor model health and performance using statistical techniques for robustness over time.
• Prototype new ML techniques to improve relevance, engagement, and monetization.

What you'll need

• 10+ years of industry experience in ML/Data Science building large-scale recommendation or personalization systems.
• Applied understanding of experimentation, metrics, and causal reasoning in real-world systems.
• Ability to take models from idea to prototype to production and business impact.
• Hands-on experience with techniques from ML, Deep Learning, NLP, Reinforcement Learning, Time Series, and Statistics.
• Strong Python programming skills with production-quality code practices.
• Experience with big data ecosystems, especially Apache Spark.
• Familiarity with cloud platforms such as AWS, GCP (Vertex AI), or Azure.

Details

• Location: Bangalore.