I
InMobi
Applied Scientist
Skills
Big DataPythonNumPyPyTorchTensorFlowMachine LearningAI
1 month ago
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Important information
Contract type:
Permanent
Salary:
$148,200 – $216,600 / year
Location:
United States
Work mode:
Onsite
Published on:
23 September 2026
What they need
- 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
- 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
- At InMobi, we’re building products that are redefining industries. Our ecosystem spans:
- InMobi Advertising – Powering data-driven mobile marketing for the world’s leading brands
- Glance – A revolutionary Gen AI-powered lockscreen & TV content platform transforming how millions discover and engage with content
- 1Weather – One of the world’s leading weather platforms, delivering precise, reliable, and real-time weather forecasts
- With deep expertise in AI, mobile, consumer technology, and digital innovation, we are home to some of the brightest minds in the industry
- What sets us apart?
- Not just what we build. How we build it. At InMobi, we balance our hunger for cutting-edge tech with a deep focus on our people - their growth, well-being, and potential- 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
- Deep grounding in one or more of:
- Online learning, bandits, RL, Bayesian methods
- End-to-end ownership: you can go from idea to production and thrive in applied settings
- Causal inference, decision theory, game theory
- Ph.D. (preferred) or Master’s degree in Computer Science, Statistics, Mathematics, Operations Research, Physics, or a related quantitative discipline
- Proficient in scientific computing with Python, including packages such as NumPy, SciPy, PyTorch, or TensorFlow
- 5.5–7 years of experience working on algorithmic or applied research problems, ideally with some production deployment experience
- A researcher’s mindset: questions first, implementation later. You are thoughtful about assumptions and rigorous about validation
- Prior experience in ad tech, marketplaces, or dynamic pricing is helpful but not required
- Statistical learning theory, optimization, probability theory, and information theory
- Comfortable working with big data platforms like Apache Spark, distributed computing, and large-scale datasets
- Strong publication record (e.g., NeurIPS, ICML, AISTATS, KDD, UAI, WSDM, EC, SODA, COLT) is a strong plus—even if not recent
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