Applied Scientist II - Recommendation
Glance (company site, opens in a new tab)2+ yrsBengaluruOn-siteDirect career pageEst. 18–35 LPA
Posted 19h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build, and deploy large-scale machine learning and recommendation systems powering personalized lock screen and live entertainment experiences on Glance.
- Manage end-to-end ML workflows including data preparation, model training, evaluation, deployment, and monitoring of model performance/drifts.
- Collaborate cross-functionally with product, design, engineering, and research teams to integrate ML and generative AI features and contribute to thought leadership.
Minimum Requirements
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Electrical Engineering, or related fields; PhD is a plus.
- At least 2 years of industry experience in machine learning/data science, preferably in large-scale recommendation systems or personalization.
- Proficiency in Python and ML frameworks (PyTorch/TensorFlow); experience with big data tools (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP).
- Experience with classical ML and deep learning techniques, recommendation algorithms, and production ML deployment are mandatory.
Ideal Candidate Profile
- Experienced with large-scale ML systems involving collaborative filtering, ranking models, embeddings, and diverse ML domains such as NLP, reinforcement learning, and time series analysis.
- Demonstrates strong capabilities in designing and deploying end-to-end ML solutions including model monitoring and performance optimization.
- Familiar with agentic AI concepts and generative models (e.g., LLMs), with a strategic approach to integrating advanced AI features into live consumer products.