Machine Learning Engineer – Ad Sciences

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 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.

The Impact You'll Make:

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

The Experience We Need:

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, o