SDE II - ML

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 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, 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.

We are looking for an SDE 2, Machine Learning to help build the core systems behind Glance's AI shopping agent. In this role, you will work on low-latency ML inference platforms, automated evaluation harnesses, and rapid 0→1 prototyping for new AI shopping features. You will also partner directly with applied scientists and backend engineers to take experimental ML models into reliable production environments.

• →ML Inference Platform: Build and scale systems running recommendation inference, vector search, feature store queries, and real-time data updates.
• →Evaluation Harness: Develop automated offline and online evaluation frameworks, regression tests, and latency/cost tracking tools to evaluate model releases.
• →Rapid Prototyping: Rapidly prototype and test new engineering ideas for the Glance AI shopping agent, turning promising concepts into scalable platform components.
• →System Performance: Optimize throughput and reduce serving latency across CPU and GPU clusters for high-volume ML workloads.

• Engineering Foundations: Strong coding skills in Python or Java, with solid background in distributed systems.
• ML Serving & Tools: Hands-on experience with model serving tools (Triton, vLLM, TorchServe), vector databases (Qdrant, Faiss), feature stores & databases.
• Evaluation Systems: Experience building testing pipelines, regression suites, or shadow deployment setups for ML services.
• Execution & Ownership: Comfortable navigating technical ambiguity, moving quickly, and shipping code in fast-paced teams.

• BTech or MTech in Computer Science, Machine Learning, or a related technical field.
• 3+ years of software engineering experience, with 2+ years focused on ML infrastructure, model serving, or recommendation systems.
• Hands-on experience deploying recommendation pipelines, vector search, or feature stores to production.
• Proficiency in Python, system profiling, and query performance tuning.
• Experience setting up model monitoring and maintaining high-throughput production ML systems.
• Ability to collaborate closely with Applied Science teams to turn models into production services.
• Self-directed, curious, and comfortable building solutions from 0→1.