ML Engineer Jobs

Lead the design and operation of secure, scalable infrastructure platforms supporting enterprise multi-GPU and multi-node AI/ML workloads. This role combines deep software engineering, cloud infrastructure, ML platform expertise, and technical leadership.

Build scalable GPU-serving and machine learning systems as a Software Engineer III on JPMorgan Chase’s Commercial and Investment Banking team. You’ll develop secure production software, improve ML serving infrastructure, and apply AI-assisted engineering tools responsibly.

Build and ship computer vision and machine learning systems that process 11 million road images daily, from raw sensor data through production inference and monitoring. You’ll work across cloud and roadside hardware to improve tolling and highway safety in the real world.

Machine Learning Engineer owning the full computer vision lifecycle, from raw sensor data and dataset curation through production deployment, monitoring, and iteration. You’ll ship models across cloud and roadside edge hardware for a tolling system processing 11 million images daily.

AI Systems Research Engineer developing production-ready machine learning systems and AI software for Bosch applications, including autonomous driving and robotics. The role bridges research and product through scalable models, infrastructure, and data pipelines.

Lead the development of large-scale BEV and multi-modal perception models that fuse camera, LiDAR, radar, and map data for autonomous trucks. This staff-level role focuses on model innovation, technical leadership, and advancing 3D perception capabilities.

Lead architecture and development for Ripple Treasury’s AI-powered cash forecasting platform, building scalable integrations, forecasting capabilities, and enterprise-grade financial systems. This Staff Software Engineer role combines hands-on software development with technical leadership, mentorship, and end-to-end ownership.

Machine Learning Engineer on Lyft’s Fulfillment team designing, deploying, and improving real-time machine learning systems for ride fulfillment and marketplace operations. The role combines applied ML research, production engineering, experimentation, and large-scale data-driven optimization.