Applied Scientist – User Intelligence

Overview of the Role:

We are looking for an Applied Scientist to develop and improve our user personalization intelligence through architectural and data research aimed at optimizing the efficacy of our targeting and pricing systems. More specifically, our team is exploring state-of-the-art attention-based architectures powered by multi-modal data, operating at InMobi's scale of trillions of events per day.

You'll join a team of experienced researchers and practitioners who have been conducting research in this space for over a decade, working closely with engineering and product counterparts to ensure research consistently translates into production and real business outcomes. InMobi maintains deep investment in the compute and infrastructure this kind of work demands — including GPU compute, training, and inference platforms. This is a rare opportunity to shape how personalization and targeting operate at truly planetary scale.

The Impact You'll Make:

• Build a pipeline of evidence-backed hypotheses and evaluate them through to a clear accept/reject decision, taking the winners to production
• Drive architectural research into attention and post-attention architectures while meeting the millisecond-level latency demanded by real-time advertising
• Advance our evaluation methodology across offline and online settings, ensuring model improvements translate into real business impact
• Leverage the breadth of data features across our product portfolio to improve our models and help guide product teams toward sourcing high-value data
• Contribute regularly to our internal model implementations, training pipelines, and documentation to help the team operate efficiently and share knowledge effectively
• Guide our infrastructure teams on medium- and long-term needs to increase our experimentation velocity
• Maintain an active research profile through external engagement — publishing, giving talks, and participating in top conferences

The Experience We Need:

• PhD in machine learning, data science, or a related field preferred; Master's degree also considered, particularly with a strong industry track record.
  • Candidates nearing graduation are also welcome to apply.
• Demonstrated expertise in machine learning/deep learning, whether through peer-reviewed publications (e.g., NeurIPS, KDD, RecSys) or through industry experience building and shipping models that performed well at scale
• Fluency in the PyTorch or JAX ecosystem, with the ability to implement complex operations in vectorized form
• Expertise in deep recommender systems, including two-tower and attention-based architectures
• Comfort with large-scale distributed data systems and the ability to build production data pipelines for training and inference
• Understanding of the ads ecosystem (OpenRTB, SSPs, DSPs, ad exchanges, MMPs) is a plus

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 (fixed) salary for this role ranges from $182,250 to $218,500 USD (min to max of base salary pay range). This salary range applies to our offices in California and New York*.

*Our ranges may vary based on the final location and region of the role 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). To encourage a spirit of shared ownership, we believe that our employees should have the ability to own a part of the organization. Furthermore, as you contribute to the growth of the company, additional stock may be issued in recognition of your contribution over time.

A quick snapshot of our benefits:

• Competitive salary and ESOP 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 a compassionate work environment 
• Flexible working hours to suit everyone 
• Wellness stipend for a healthier you!      
• Free lunch 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 Applied Scientist will advance user personalization models for targeting and pricing, with an emphasis on attention-based architectures and multimodal data. The work spans research, evaluation, and production implementation for real-time advertising systems at very large scale.

Role at a glance

Skills mentioned

What you will likely work on

• Develop and test evidence-backed hypotheses, then move successful approaches into production.
• Research attention and post-attention architectures that meet millisecond-level latency needs.
• Improve offline and online evaluation methods and connect model gains to business outcomes.
• Use product data features to improve models and advise product teams on valuable data sources.
• Contribute to model implementations, training pipelines, and technical documentation.
• Advise infrastructure teams on medium- and long-term needs for faster experimentation.
• Share research through publications, talks, and participation in leading conferences.

Good fit signals

• Demonstrated machine learning and deep learning expertise through research publications or shipped models that performed well at scale.
• Strong background in deep recommender systems, including two-tower and attention-based architectures.
• Fluency with PyTorch or JAX and ability to implement complex vectorized operations.
• Comfort working with distributed data systems and production training and inference pipelines.
• Understanding of advertising ecosystem components is a plus; candidates nearing graduation are welcome.