Applied Scientist III - Recommendation Systems
Glance (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 30–55 LPA
Posted 19h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and deploy large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
- Build and operate agentic AI systems that autonomously monitor, experiment, and improve ML workflows with minimal human intervention, using LLMs, embeddings, and reinforcement learning.
- Collaborate cross-functionally to integrate ML and generative AI-driven features into consumer experiences and contribute to ML/AI thought leadership.
Minimum Requirements
- 6+ years of industry experience in ML/Data Science with a focus on large-scale recommendation systems or personalization.
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields; PhD is a plus.
- Proficient in Python and ML frameworks (PyTorch, TensorFlow), big data tools (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP).
- Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems; Work Experience Required: 6+ years
Ideal Candidate Profile
- Experienced in end-to-end ML solution design and production deployment in large-scale recommendation and personalization systems.
- Skilled in integrating classical ML, deep learning, NLP, reinforcement learning, and agentic AI approaches to build autonomous, self-improving workflows.
- Comfortable working in cross-functional teams with strong communication skills to simplify and align complex ML concepts across product and business stakeholders.