Applied Scientist II - Recommendation Systems
Core
Design, build, and deploy large-scale recommendation systems and intelligent ML models powering personalized lock screen and live entertainment experiences on Glance AI's commerce platform.
Role type
Applied Scientist II (Recommendation Systems & ML)
Builds
Personalized discovery interfaces, ranking models, and content understanding systems for mobile and smart TV ecosystems.
Domain
E-commerce, AI/ML, Recommendation Systems
Deliverable
production ML models
Required skills
Large-scale recommendation systems, classical machine learning, deep learning, NLP, sequence modelling, reinforcement learning, time series, statistical modelling, ranking algorithms, big data processing, cloud computing, Python, PyTorch/TensorFlow, Spark, distributed data systems
Preferred skills
LLMs, generative models, agentic/autonomous AI workflows, privacy-preserving ML, identity-less ecosystems
Technologies
Vertex AI, Gemini, Imagen, Spark, Hadoop, Azure, AWS, GCP, PyTorch, TensorFlow, NumPy, SciPy, R
Responsibilities
Design and develop large-scale recommendation systems using advanced ML and deep learning; Build and operate machine learning models on diverse, high-volume data sources; Develop rapid experimentation workflows to validate hypotheses; Own data preparation, model training, evaluation, and deployment pipelines; Monitor ML model performance using statistical techniques to identify drifts and failure modes.
Seniority
Mid-Senior, hands-on IC