Applied Scientist III

InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real‑time context into business outcomes, delivering results grounded in privacy‑first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact.

Through Glance AI, we are shaping AI Commerce, reimagining the future of e‑commerce with inspiration‑led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences.

With rich first‑party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide.

Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company’s Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including Soft Bank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond.

At InMobi Advertising, you’ll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit

We are looking for an Applied Scientist III to join our algorithmic and research science team. You’ll work on mathematically rigorous, research‑driven problems at production scale. This role sits at the intersection of theory and application, designing algorithms that combine elegant modeling with measurable business impact. Specifically, our scientists tackle challenges across traffic shaping, fraud detection, ad quality, pricing strategies, and auction theory, along with their practical applications.

We leverage the latest deep learning models alongside classical machine learning techniques to build innovative solutions.

As the heart of the InMobi Exchange, our team optimizes the company’s core business functions and creates the strategic moat that sets us apart in the market. You will not just “use models”—you will formulate them, evaluate their assumptions, tailor them to our problem domain, and bring them to life in production. Many of our challenges have no off‑the‑shelf solutions; we require scientific creativity to bridge research and reality.

If you thrive on solving complex, high‑impact problems and want to see your ideas shape the future of a global exchange, this is the place where your work will truly make a difference.

In this role, you’ll operate at the intersection of cutting‑edge research and massive‑scale production, shaping algorithms that power a global advertising marketplace, making tens of trillions of real‑time decisions every day. You’ll work in an environment where models are continuously tested, evaluated, and refined—with rapid learning loops measured in hours, not weeks. Collaborating with a team that values algorithmic depth and scientific rigor, you’ll have the opportunity to prototype, publish, and deploy work that drives measurable business impact.

• Formulate, analyze, and implement algorithms that power real‑time auctions, dynamic pricing, bid shaping, pacing, and traffic allocation across a massive‑scale ad marketplace.
• Design and experiment with methods in online learning, reinforcement learning, multi‑armed bandits, forecasting, game theory, and Bayesian modeling—in non‑stationary, adversarial environments.
• Collaborate with product and engineering teams to deploy your models in production and run real‑world experiments with rapid feedback loops (measured in hours, not weeks).
• Contribute to the…