Description :

In this role, you would own personalisation and recommendation end-to-end, setting the vision, designing core ML systems, and pushing beyond traditional approaches toward intent-aware, contextual, and generative intelligence.

You would lead a team of 8-10 ML engineers and researchers, building large-scale, low-latency systems that directly power user experience and monetisation. This includes core recommendations and ranking, as well as ML-driven ad optimisation spanning relevance, creative selection, pacing, bidding, and long-term user value optimisation.

The problem space covers user and advertiser modelling, representation learning, exploration-exploitation, causal measurement, and online learning, with a strong emphasis on balancing engagement, revenue, and user trust. This is a role where ML leadership defines the product, not just optimises a subsystem. At Glance, you'd build systems that millions of users interact with daily, often without opening an app, creating a durable technical moat, scaling a world-class team, and shaping AI-driven discovery at scale.

Requirements :

- PhD or Master's in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research, Economics, Analytics, or Data Science. Or a Bachelor's with additional experience.

- 8 to 10 years of experience working in ML / DS teams.

- You would have applied algorithms and techniques such as NLP, Reinforcement Learning, Time Series, etc., from Machine Learning, Deep Learning, and Statistics or other domains, in solving real-world problems and understanding the practical issues of using these algorithms, especially on large datasets.

- You should be comfortable with software programming and statistical platforms such as Tensorflow, PyTorch, scikit-learn, etc., etc.

- You should be comfortable with using one or more distributed training technologies such as Apache Spark, RAPIDS, dask, etc., along with mlops stack such as Kubeflow, MLFlow, or their cloud counterparts.

- Comfortable collaborating with cross-functional teams.

- Excellent technical and business communication skills, and should know how to present technical ideas in a simple manner to business counterparts.

- Possess a high degree of curiosity and the ability to rapidly learn new subjects.