Machine Learning Engineer (Ad Sciences)

Join InMobi, a leading player in the ad tech industry, as a Machine Learning Engineer. In this role, you will develop and optimize ad science models, open-source LLMs, and the infrastructure that supports them. You will work closely with experienced researchers and engineers, contributing to cutting-edge research and building scalable solutions. This is an opportunity to shape the future of ad intelligence at a massive scale.

- Develop and optimize ad science models, open-source LLMs, and the underlying infrastructure. - Build and support training pipelines and model implementations that maximize experimentation velocity. - Collaborate closely with Applied Scientists on active research, contributing directly to experiment design and modeling.

- Master's degree in machine learning or a related field required; a PhD is a plus - Knowledge of reinforcement learning systems — including RL approaches, reward signals, and post-training feedback loops — is a plus - Expertise in large-scale distributed data systems, including high-performance relational and key-value stores, orchestrators like Airflow, and data transformations in Spark - Knowledge of deep recommender systems, including two-tower and attention-based architectures, is a plus - Understanding of the ads ecosystem (OpenRTB, SSPs, DSPs, ad exchanges, MMPs) is a plus - Experience with cloud platforms and container orchestration using Kubernetes - Expertise in Python; familiarity with Java (especially in high-performance serving systems) is a plus - Expertise in PyTorch or a similar ecosystem - Experience with accelerator-based inference systems such as Triton, and optimization backends like ONNX and TensorRT - At least 3 years of experience as a Machine Learning Engineer, building state-of-the-art machine learning/deep learning systems at extreme scale