Applied Scientist II (Recommendation Systems)

TL;DR

Applied Scientist II (Recommendation Systems): Designing and deploying large-scale recommendation systems for personalized lock screen and entertainment experiences with an accent on classical ML, ranking algorithms, and deep learning. Focus on building agentic AI systems, optimizing personalization pipelines, and validating hypotheses through rapid experimentation.

Company

AI commerce platform transforming screens into personal discovery stages through proprietary models integrated with Google’s AI platforms.

What you will do

• Design and develop large-scale recommendation systems using advanced ML, ranking algorithms, and statistical modeling.
• Build and operate ML models on high-volume data for personalization and content understanding.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering.
• Collaborate with UX Researchers, Product Managers, and Software Engineers to integrate GenAI-driven features into consumer experiences.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related fields.
• 3+ years of industry experience in ML/Data Science, specifically in large-scale recommendation systems or personalization.
• Expertise in algorithms for NLP, Reinforcement Learning, Time Series, and Deep Learning.
• Proficiency in Python and statistical tools (NumPy, SciPy, PyTorch, or TensorFlow).
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).

Nice to have

• PhD degree in a relevant field.
• Experience building or experimenting with LLMs, generative models, and agentic AI workflows.

Culture & Benefits

• Collaborative, multi-functional team including engineers, physicists, economists, and social scientists.
• Opportunity to contribute to AI thought leadership through blogs, case studies, and industry conferences.
• High-impact role within a company backed by global leaders like Google and Jio Platforms.