Machine Learning Engineer, InMobi
Ad Sciences
$172.5-210k
+ Equity
2+ days a week in office (San Mateo, CA)
Data-driven mobile marketing platform
Be an early applicant
Data-driven mobile marketing platform
1001+ employees
Be an early applicant
$172.5-210k
+ Equity
2+ days a week in office (San Mateo, CA)
1001+ employees
Company mission
To drive real connections between brands and consumers through its data-driven mobile advertisement platform.
Role
Who you are
- Master's degree in machine learning or a related field required; a PhD is a plus
- At least 3 years of experience as a Machine Learning Engineer, building state-of-the-art machine learning/deep learning systems at extreme scale
- Expertise in large-scale distributed data systems, including high-performance relational and key-value stores, orchestrators like Airflow, and data transformations in Spark
- Expertise in Python; familiarity with Java (especially in high-performance serving systems) is a plus
- Expertise in PyTorch or a similar ecosystem
- Experience with accelerator-based inference systems such as Triton, and optimization backends like ONNX and TensorRT
- Experience with cloud platforms and container orchestration using Kubernetes
- Knowledge of deep recommender systems, including two-tower and attention-based architectures, is a plus
- Knowledge of reinforcement learning systems — including RL approaches, reward signals, and post-training feedback loops — is a plus
- Understanding of the ads ecosystem (OpenRTB, SSPs, DSPs, ad exchanges, MMPs) is a plus
What the job involves
- We are looking for a Machine Learning Engineer to develop and optimize our ad science models, open-source LLMs, and the underlying infrastructure that powers them — with a constant eye toward performance and cost
- AI and ML sit at the core of InMobi's business, and our science teams are tackling some of the field's most interesting problems: creative optimization, user personalization, targeting, yield management, traffic shaping, and more
- We're moving fast and deep into architectural research, generative AI adoption, compute scaling on the latest accelerators (GPUs/TPUs), and advances in reinforcement learning
- You'll join a team of experienced researchers and engineers who have been pushing the boundaries of ad science research for over a decade, working closely with data and platform engineering to build solutions that scale and serve the needs of every science team across the organization
- This is a chance to shape the infrastructure and models behind ad intelligence operating at truly massive scale
- Build and support training pipelines and model implementations that maximize experimentation velocity
- Adapt open-source LLM infrastructure like DeepSpeed and OpenRLHF to meet InMobi-specific post-training needs
- Optimize online and batch inference for low latency and cost efficiency
- Build monitoring and evaluation solutions that keep our infrastructure reliable and our models behaving as expected
- Leverage the breadth of data features across our product portfolio to strengthen our data pipelines and unlock new features for training and inference
- Explore new platforms and ecosystems (e.g., JAX on TPUs) to help diversify our compute
- Collaborate closely with Applied Scientists on active research, contributing directly to experiment design and modeling
Our take
Mobile advertising is an incredibly important element of marketing campaigns for modern businesses, but success is limited to the quality of engagements that campaigns have with audiences. Engagement can be optimised by targeting ads to relevant audiences through cookies and other data sets, but without the right analytic tools to lead to actionable insights, this data remains useless.
InMobi provides a data-driven mobile marketing platform, offering a toolkit called InMobi Pulse that provides insights into mobile marketing based on consumer feedback, product testing, and other proprietary data. The company also provides InMobi Exchange, a platform for reaching mobile-first audiences and an enterprise-grade platform for purchasing DSP services.
Whilst it is undeniable that InMobi faces competition from other mobile-focused marketing platforms, the company stands out with the sheer range of tools it offers and its focus on markets such as India and Southeast Asia, which are difficult for North American and European firms to enter. InMobi has plans to further expand globally, however, and is bringing its Glance lock screen advertising product to the US and Latin America in the near future.
Freddie
Company Specialist at Welcome to the Jungle
Insights
2% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Jul 2025
$3.7m
LATE VC
Dec 2014
$5m
SERIES C
Total funding: $224.3m
Company HQ
Central Water Catchment, Singapore
Leadership
Abhay Singhal
(Co-Founder & CEO (InMobi Advertising))Since co-founding InMobi in 2006, they have held a number of roles at the company, including Head of Global Ad Sales, MD, CRO, and now CEO. Previously co-founded TeN where they served as the Head of Sales for over 4 years.
Piyush Shah
(Co-Founder & COO (Glance))Experience as co-founder and Head of Business Development for LearningSpiral.com Pvt Ltd. Previously also a Product Manager of Consumer Payments and Assistant Vice President of Private Banking for Deutsche Bank.
Naveen Tewari
(Co-Founder & CEO (InMobi & Glance))Founder and CEO of Glance. Previously spent 3 years as an Associate at McKinsey & Company.
Mohit Saxena
(Co-Founder & CTO (InMobi))Senior Columnist for The Indian Economist since 2015. Previously founded Rizort.
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