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

What You Will Be Doing

Design and implement production-ready generative AI applications that serve millions of users, from initial architecture through deployment and monitoring
Build advanced RAG (Retrieval-Augmented Generation) pipelines that combine vector databases, hybrid search, and intelligent caching to deliver sub-second response times
Develop multimodal AI systems that seamlessly integrate text, vision, and audio capabilities using state-of-the-art models
Architect scalable microservices that handle thousands of concurrent AI requests while optimizing for cost, latency, and reliability
Lead code reviews and technical design sessions, establishing best practices and architectural patterns that elevate the entire team's capabilities
Optimize large language models through fine-tuning techniques to achieve domain-specific performance improvements
Implement comprehensive MLOps practices including automated testing, model versioning, A/B testing frameworks, and real-time monitoring dashboards
Collaborate with product managers and stakeholders to translate complex business requirements into innovative AI solutions
Deploy AI models across multiple cloud platforms (GCP) using containerization and orchestration technologies
Create and maintain technical documentation, runbooks, and architectural decision records that enable knowledge sharing across teams
Mentor junior engineers through pair programming, technical talks, and hands-on guidance to accelerate their growth
Research and prototype emerging AI technologies to identify opportunities for competitive advantage

Gen AI Responsibilities

Fine-tune and optimize state-of-the-art language models for specific business use cases, achieving significant improvements in accuracy and relevance
Design multi-agent AI systems using frameworks to orchestrate complex workflows and decision-making processes
Implement advanced prompt engineering strategies including Tree of Thoughts, ReAct patterns, and automatic prompt optimization to maximize model performance
Build production-grade embedding systems that handle billions of vectors, implementing efficient indexing strategies and hybrid search capabilities
Develop computer vision pipelines using models for tasks ranging from object detection to visual question answering
Create secure AI applications with robust safeguards against prompt injection, jailbreaking, and data leakage while maintaining compliance with AI governance standards
Optimize token usage and implement intelligent caching strategies to reduce costs by 50-70% while maintaining quality
Design and implement evaluation frameworks that go beyond traditional metrics, incorporating human feedback loops and domain-specific quality measures
Build real-time AI inference systems capable of processing streaming data with sub-100ms latency requirements
Integrate multiple foundation models into unified applications, implementing fallback mechanisms and load balancing for high availability
Develop custom tools and functions that extend LLM capabilities, enabling models to interact with databases, APIs, and external systems
Implement advanced RAG techniques including contextual embeddings, cross-encoder reranking, and Graph RAG for complex reasoning tasks
Create multimodal search systems that enable users to query across text, images, and documents using natural language
Build AI-powered data processing pipelines that automatically extract, transform, and enrich unstructured data at scale
Deploy edge AI solutions using frameworks like ONNX and TensorRT, optimizing models for resource-constrained environments

What We're Looking For

5+ years of hands-on experience building and deploying ML/AI systems, with at least 2+ years focused on generative AI and LLMs
Expert-level Python programming skills with deep knowledge of async programming, multiprocessing, and performance optimization
Strong experience with modern AI frameworks including PyTorch, Transformers, LangChain, and vector databases
Proven track record of deploying AI applications to production environments serving real users at scale
Deep understanding of transformer architectures, attention mechanisms, and the latest advances in generative AI
Experience with cloud platforms (GCP) and containerization technologies (Docker, Kubernetes)
Excellent communication skills with the ability to explain complex AI concepts to both technical and non-technical audiences
Proven experience improving large-scale product search and discovery — including dense retrieval with bi-encoders, cross-encoder reranking, query understanding, and hybrid BM25 + vector search across catalogs of tens of millions of SKUs
Hands-on experience building and deploying production multi-agent systems using orchestration frameworks such as LangGraph and Google ADK — designing stateful, tool-augmented agents for complex, real-world workflows
Bachelor's degree in Computer Science, Mathematics, or related field (Master's preferred but not required with relevant experience)

Nice to Have

Published research papers or significant contributions to open-source AI projects
Experience with multimodal AI systems combining vision, language, and audio
Domain expertise in specific verticals (healthcare, finance, legal, e-commerce)
Knowledge of AI safety, alignment, and constitutional AI principles
Experience building AI infrastructure and platforms used by other engineers
Familiarity with emerging technologies like neural architecture search, mixture of experts, or neuromorphic computing

The InMobi Culture

At InMobi, culture isn't a buzzword; it's an ethos woven by every InMobian, reflecting our diverse backgrounds and experiences.

We thrive on challenges and seize every opportunity for growth. Our core values — thinking big, being passionate, showing accountability, and taking ownership with freedom — guide us in every decision we make.

We believe in nurturing and investing in your development through continuous learning and career progression with our InMobi Live Your Potential program.

InMobi is proud to be an Equal Employment Opportunity employer and is committed to providing reasonable accommodations to qualified individuals with disabilities throughout the hiring process and in the workplace.

Visit https://www.inmobi.com/company/careers to better understand our benefits, values, and more!

SDE III Gen AI.