Applied Scientist II - Recommendation

Glance

Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV — shaping the new era of shopping. Glance is operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of global technology leader InMobi, and is backed by Mithril Capital, Google and Jio Platforms. To learn more, visit glance.com.

InMobi

InMobi Group is a global technology company shaping the future of agentic commerce and advertising. Through its ecosystem of businesses — including InMobi Advertising and flagship consumer platform Glance — InMobi leverages data, machine learning, and generative AI to help brands reach audiences more precisely and consumers discover products more intuitively. Glance, which is pioneering new models of agentic commerce, is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd.

InMobi Advertising

InMobi Advertising, part of global technology company InMobi, is an agentic advertising platform helping brands and merchants achieve their business outcomes. Through its proprietary intelligence, AI-led solutions, and vast consumer reach — including flagship consumer platform Glance — InMobi Advertising delivers the omnichannel performance defining what's next in advertising and commerce. Glance is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. To learn more, visit advertising.inmobi.com.

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning , large-scale recommendation systems , and modern agentic AI systems .

You will design, build, and deploy intelligent systems that power Glance’s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include

Classical ML & Recommendation Systems

• Design and develop large-scale recommendation systems using advanced ML, statistical modelling, ranking algorithms, and deep learning.

• Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, 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 counterparts.

• Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.

Cross-functional impact

• Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance’s consumer experiences.

• Contribute to Glance’s ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.

• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.

• Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.

We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.

You should have experience with

• Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).

• Classical ML and deep learning techniques across NLP, sequence modelling, RL, clustering, and time series.

• Experience in deploying ML workflows/models in production system

• Big data processing (Spark, distributed data systems) and cloud computing.

• Designing end-to-end ML solutions—from prototype to production.

• Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).

Qualifications

• Bachelor’s/master’s in computer science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.

• 2+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.

• Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.

• Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.

• Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).

• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).

• Comfortable working in cross-functional teams.

• Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).

• Excellent communication skills with the ability to simplify complex technical concepts.

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

Our team includes engineers, physicists, economists, mathematicians, and social scientists—a great data scientist can come from anywhere.

Since 2019, Glance has built the extraordinary. Beyond just technology. It has built a way of working.

Across 5 offices in around 3 countries, through every pivot and breakthrough, one thing has remained constant: we are builders, dreamers, doers. We are fluid enough to move fast, grounded enough to own outcomes, and human enough to care deeply about the work and about one another.

Culture is at the core of that ethos. It has been co-created by the people who built this company and by those continuing to shape it every day. It lives in how we work, how decisions are made, how teams show up for one another, and how seriously we take the responsibility to build the best.

This is a place where ambition and belonging occupy the same space. Where the bar is high and the support is real. Where freedom comes with trust, and trust comes with accountability. Where you are valued not only for what you do, but for the perspective, judgment and humanity you bring to the work. Where you will be challenged by the work and supported by the communities, passions and experiences that shape who you are beyond your role.

If this sounds like the place you have been looking for, join us.