SDE III - Machine Learning

Skills this role screens for

About the role

Glance

Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV — shaping the new era of shopping. Glance is operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of global technology leader InMobi, and is backed by Mithril Capital, Google and Jio Platforms. To learn more, visit glance.com.

InMobi

InMobi Group is a global technology company shaping the future of agentic commerce and advertising. Through its ecosystem of businesses — including InMobi Advertising and flagship consumer platform Glance — InMobi leverages data, machine learning, and generative AI to help brands reach audiences more precisely and consumers discover products more intuitively. Glance, which is pioneering new models of agentic commerce, is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd.

InMobi Advertising

InMobi Advertising, part of global technology company InMobi, is an agentic advertising platform helping brands and merchants achieve their business outcomes. Through its proprietary intelligence, AI-led solutions, and vast consumer reach — including flagship consumer platform Glance — InMobi Advertising delivers the omnichannel performance defining what's next in advertising and commerce. Glance is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. To learn more, visit advertising.inmobi.com.

SDE 3, Machine Learning

The work

About the Role

We are looking for an SDE 3, Machine Learning to lead the technical architecture for Glance's AI shopping agent. You will own the core engineering for our ML Inference Platform, Evaluation Harnesses, and rapid 0→1 prototyping frameworks. In this role, you will set technical standards, design reliable distributed ML systems, and work across teams to scale complex agentic workflows.

The work

What You Will Own & Build

• Inference Platform Architecture: Architect low-latency recommendation inference systems, distributed vector search, feature store integrations, and real-time streaming updates.
• Evaluation Infrastructure: Build comprehensive offline and online evaluation pipelines, golden dataset testing tools, tool-call tracking, and automated regression suites.
• Agentic Core & New Initiatives: Lead the engineering execution for rapid 0→1 prototyping of AI shopping agent features—building flexible orchestration runtimes, tool registries, and gateway middleware.
• Technical Leadership: Partner with Applied Science, Product, and Data Platform teams to translate complex research concepts into clean, production-grade systems.

Who they want

What We Are Looking For

You might thrive in this role if you have:

"Glance collects and processes personal data such as your name, contact details, resume and other information that may contain personal data for the purpose of processing your application. Glance utilizes Greenhouse, a third-party platform. Please review Greenhouse's Privacy Policy to understand how the data collected from you is processed and managed. By clicking on 'Submit Application', you acknowledge and agree to the above privacy terms. Should you have any privacy concerns, you may contact us through the details mentioned in your application confirmation email."

• System Architecture: Track record of designing, building, and scaling distributed ML systems and production serving pipelines.
• Deep ML Systems Knowledge: Experience with model optimization (quantization, TensorRT, torch.compile), vector search indexing, and real-time feature delivery.
• Agent & LLM Infrastructure: Understanding of LLM orchestration, agentic tool-use harnesses, and multimodal model serving.
• Technical Influence: Ability to mentor engineers, guide design reviews, and raise the engineering bar across teams.
• BTech or MTech in Computer Science, Machine Learning, or a related quantitative field.
• 6+ years of software engineering experience, with 5+ years dedicated to ML platforms, inference engines, or recommendation systems.
• Expertise in building high-throughput, low-latency recommendation inference, vector search, and feature serving infrastructure.
• Proficiency in Python or Java, and production ML tools across PyTorch, Triton, and distributed frameworks (Ray/Spark).
• Experience architecting automated evaluation harness suites and production monitoring for ML systems.
• Strong communication skills—able to simplify complex systems and align stakeholders across product and engineering.
• Self-directed, curious, and comfortable driving ambiguous 0→1 technical initiatives.