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InMobi

Applied Scientist III

San Mateo, CA · onsite
Company's own boardMaster's degree5–7 yrs

First seen Sep 22 · seen live today · from InMobi's own Greenhouse board

Skills mentioned

pythongosparkpytorchmachine learning

The posting, as published

InMobi (Corporate) 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. 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. Overview of the Role: 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. Location : This role is based on-site in our San Mateo, CA office The Impact You'll Make: 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 scientific community by publishing high-quality research, conducting internal seminars, and staying abreast of advances in machine learning, algorithms, and applied statistics. Evaluate the long-term dynamics of deployed algorithms, incorporating feedback, exploitation-exploration trade-offs, and incentives within multi-agent systems. Identify new areas for innovation by translating business challenges into research questions and proposing novel, high-impact methodologies. Translate mathematical ideas into practical, high-performance algorithms that operate at scale in production environments. Explore and close the loop between model predictions and real-world outcomes, refining algorithms based on system behavior. The Experience We Need: Ph.D. (preferred) or Master’s degree in Computer Science, Statistics, Mathematics, Operations Research, Physics, or a related quantitative discipline. 5.5–7 years of experience working on algorithmic or applied research problems, ideally with some production deployment experience. Deep grounding in one or more of: Statistical learning theory, optimization, probability theory, and information theory Causal inference, decision theory, game theory Online learning, bandits, RL, Bayesian methods Strong publication record (e.g., NeurIPS, ICML, AISTATS, KDD, UAI, WSDM, EC, SODA, COLT) is a strong plus—even if not recent. Proficient in scientific computing with Python, including packages such as NumPy, SciPy, PyTorch, or TensorFlow. Comfortable working with big data platforms like Apache Spark, distributed computing, and large-scale datasets. A researcher’s mindset: questions first, implementation later. You are thoughtful about assumptions and rigorous about validation. End-to-end ownership: you can go from idea to production and thrive in applied settings. Prior experience in ad tech, marketplaces, or dynamic pricing is helpful but not required. At InMobi, you’ll be surrounded by people who… Think big and act fast: We’re entrepreneurial, thrive in ambiguity, and love solving high-impact problems Are passionate, fanatically driven, and take immense pride in their work: We care deeply about the impact we create and continuously push our potential Own their outcomes: We take responsibility, make bold decisions, and execute with confidence Embrace freedom with accountability: We value autonomy and understand that trust comes with responsibility Believe in lifelong learning: We welcome feedback, challenge ourselves to grow, and aren’t afraid to take smart risks Award-winning culture, best-in-class benefits Our compensation philosophy enables us to provide a competitive salary that drives high performance while balancing business needs and pay parity. We determine compensation based on a wide variety of factors, including role, nature of experience, skills, and location. The base salary (fixed) for this role ranges from $148,200 USD to $216,500 USD (min to max of base salary pay range). This salary range is applicable for our offices located in California and New York * . *Our ranges may vary based on the final location or region of the roles in accordance with the geographical differentiation in pay scales in the country. In addition to cash compensation, based on the position, an InMobian can receive equity in the form of Employee Stock Options (ESOPs). We believe that our employees/personnel should have the ability to own a part of the entity they are a part of. Therefore, the entity employing you may elect to provide such stock to you. Ownership of stock enables us to treat our employer company as our own and base our decisions on the company’s best interests. To encourage a spirit of shared ownership, we grant InMobians relevant company stock(s). As you contribute to the growth of your company, certain stocks may be issued to you in recognition of your contribution. A quick snapshot of our U.S. benef

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