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About This Role
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 SoftBank, 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 www.inmobi.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.
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.
What we build…
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.
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) pay range for this role would range from $148,200 USD to $216,600 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 Restricted Stock Units. 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 stocks to you. Ownership of stock enables us to treat our employer company as our own and base our decisions on the company's best interest at heart. 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. benefits:
- Competitive salary and RSU grant (where applicable)
- High\-quality medical, dental, and vision insurance (including company\-matched HSA)
- 401(k) company match
- Generous combination of vacation time, sick days, special occasion time, and company\-wide holidays
- Substantial maternity and paternity leave benefits and compassionate work environment
- Flexible working hours to suit everyone
- Wellness stipend for a healthier you!
- Free lunch is provided in our offices daily
- Pet\-friendly work environment and robust pet insurance policy \- because we love our animals!
- Employee Assistance Program (EAP)
If this sounds like the kind of team, role, values, benefits, and challenges that excite you, we'd love to hear from you.Go for it!
InMobi is an equal opportunity employer
InMobi is a place where everyone can grow. Howsoever you identify, and whatever background you bring with you, we invite you to apply if this sounds like a role that would make you excited to work.
*InMobi provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.*
The InMobi Culture
At InMobi, culture isn't a buzzword; it's an ethos woven by every InMobian, reflecting our diverse backgrounds and experiences.
We thrive on challenges and seize every opportunity for growth. Our core values — thinking big, being passionate, showing accountability, and taking ownership with freedom — guide us in every decision we make.
We believe in nurturing and investing in your development through continuous learning and career progression with our InMobi Live Your Potential program.
InMobi is proud to be an Equal Employment Opportunity employer and is committed to providing reasonable accommodations to qualified individuals with disabilities throughout the hiring process and in the workplace.
Visit https://www.inmobi.com/company/careers to better understand our benefits, values, and more!
Salary Context
This $148K-$216K range is below the median for Research Scientist roles in our dataset (median: $183K across 83 roles with salary data).
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 3,708 AI roles we're tracking, Research Scientist positions make up 3% of the market. At InMobi, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 197 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($182K) sits 18% below the category median. Disclosed range: $148K to $216K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
InMobi AI Hiring
InMobi has 1 open AI role right now. They're hiring across Research Scientist. Based in San Mateo, CA, US. Compensation range: $216K - $216K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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