…It’s an opportunity to bridge state‑of‑the‑art ML with meaningful biomedical impact in a highly collaborative research environment . Responsibilities Design, execute…

…you will partner with Research, Engineering, Go-to-Market, Security, Legal, Privacy, and government mission, acquisition, and technical stakeholders to align on scope, remove…

…Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About…

…Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About…

…in evaluation as a research discipline — not just a stepping stone to a model-building role. - Background in CS, ML, statistics, or an adjacent…

…You - Have 3+ years leading or managing engineers, in AI/ML infrastructure or another large-scale compute environment. - Have owned production systems with real…

…You will partner directly with Applied Scientists to translate research into production-grade inference pipelines. You will own the full lifecycle of ML model…

…field data Develop and evaluate ML and control systems for on-device management Rapidly prototype end-to-end systems, from data analysis to device…

…Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About…

…testing appropriate distributions, testing the assumptions behind frequentist stats Proficient in using a statistical scripting language and data science/ML packages (e.g. python…

…Experience leading and managing a team of software engineers. Experience in one or more of the following areas: AI/ML, platform development, distributed systems…

…systems. - Experience with Customer Success, customer education, or marketing-automation platforms (Gainsight, Vitally, ChurnZero, or similar) and product analytics tools. - Experience in AI, ML…

…the algorithms, design choices, and trade-offs, on both the ML and the systems sides. - Experience training large models across many accelerators, with comfort…

…Collaborate cross-functionally with ML researchers, software engineers, and external clinical partners across Mountain View, London, and Paris. Publish original research in top machine…

…Engineer (PE). Experience in a high-tech, fast-paced environment with the ability to prioritize multiple and changing initiatives. Understanding of AI/ML tools…

…Experience with experimentation, dataset curation, eval systems, and building ML pipelines. Experience with machine learning, computer vision, and deep learning. One of more scientific…

…layer, and excessive agency in multi-agent systems, translating emerging threats into concrete mitigations with Engineering and Product. Shape Ripple's external AI security…

…specific focus on TPU architecture and its integration within AI/ML-driven systems. The AI and Infrastructure team is redefining what’s possible. We…

…systems, proactively anticipating scaling bottlenecks or shifts in usage as LLMs become increasingly complex. Coordinate efforts across multiple groups, including Android ML, ML Compiler…

…release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified…

…Within AI2, we are CBS - Core ML, Compute infrastructure and Spatial Flex organization whose mission is to provide the most cutting-edge AI by…

…This role is within the Research Engineering team at MSR Cambridge . Our team has broad experience spanning front-end, systems, networking and ML engineering…

…large language models and specialized Machine Learning (ML) hardware developed by Google. The Google Cloud AI Research team addresses AI challenges motivated by Google…

…Lead and program manage e2e engineering development and landing of next-gen ML TPU systems through NPI PLC process from concept to production and…

…Demonstrated expertise in solving complex technical challenges in one or more domains such as distributed systems, AI/ML infrastructure, developer platforms, or cloud services…