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 dĂ©cor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first-party data and unparalleled consumer access, it harnesses InMobiâs 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 Companyâs 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, youâll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com Key Responsibilities
ML Platform Architecture: Design and scale distributed ML platform for data, feature store, training, and inferencing; build multi-region, containerized infrastructure using Kubernetes and Terraform. Training & Inferencing at Scale: Optimize GPU/TPU/CPU utilization for large-scale training and real-time inferencing; implement distributed training, model parallelism, and caching with Ray. Performance & Governance: Drive FinOps-aligned architecture, auto-scaling, and efficiency; enable observability, SLA/SLO tracking, and incident management. Collaboration & Leadership: Partner with cross-functional teams to deliver high-impact ML solutions; mentor engineers and set best practices for ML systems design.
Technology Stack
ML Frameworks: TensorFlow, PyTorch Serving: Triton, TensorFlow Serving, TorchServe Distributed Compute: Ray, Kubernetes, Spark, GPU/TPU optimization Lifecycle: MLflow and AirFlow Infra: AWS/GCP/Azure, Terraform, CI/CD
What Weâre Looking For
8â12 years in ML platform/distributed systems. Strong in Python, Kubernetes, GPU/TPU optimization. Proven ability to design fault-tolerant, high-throughput ML systems.
The InMobi Culture At InMobi, culture isnât 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 â thinking big, being passionate, showing accountability, and taking ownership with freedom â 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!