Jobs
Indexed directly from employers. Every age is their own publish date.
Indexed directly from employers. Every age is their own publish date.
Indexed directly from employers. Every age is their own publish date.
Searching titles and descriptions for “Staff ML Engineer, Generative Model Performance & Efficiency”. A match may be a passing mention rather than the job itself. Titles only.
57 roles across 61 listings · show every listing · page 1 of 3
…Define and refine requirements for generating high-quality, dense, and broad human feedback to optimize ML models performance. Partner with Engineering to design, test…
…The scheduler deciding what runs next, models predicting cycle time and demand, systems interpreting engineering drawings, analytics tracking production, and operators understanding what is…
…More connected assets generate more data, more data trains better models, better models drive more value, and more value wins more assets. The market…
…and enhancing AI models, focusing on efficiency, precision, and scalability. Daily activities include ensuring data quality, monitoring model performance, and generating actionable insights from…
…financial operating models Extraordinary problem-solving and critical thinking abilities to come up with new frameworks for assessing profitability and capital efficiency in a…
…with engineering teams to integrate models into real-time systems, ensuring reliability, uptime, and quality at scale. - Drive improvements in inference efficiency, model serving…
…a wide range of models on AWS's custom ML accelerators, supporting novel architectures while maximizing their training performance. Working across the stack from…
…record in top-tier AI/ML conferences and deep expertise in generative AI, including Multi-Modal Foundation Models, Efficient Architectures, LLM Reasoning, Reinforcement Learning…
…time model adaptation, bringing cutting-edge advancements into production. Partner with ML infrastructure teams to build high-performance, distributed training systems that efficiently scale…
…ML model lifecycles from data generation to on-road validation. Maintain an in-house ML inference platform to serve large language models efficiently. Maintain…
…As a performance engineer in the ML Compute Efficiency team, you’ll tackle ambiguous systems challenges, identify inefficiencies and build solutions that maximize accelerator…
…ML-driven systems. As a Senior Staff Co-Design Engineer on the TPU Chip Architecture team, you will bridge the gap between model architecture…
…Your technical leadership will directly shape the efficiency, scalability, and performance of Google's hyperscaler platform for next-generation AI/ML training and inference…
…Drive automation and observability improvements, using metrics and analytics — including AI workload quality signals and model performance telemetry — to improve performance, reliability, and efficiency…
…Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About…
…a wide range of models on AWS's custom ML accelerators, supporting novel architectures while maximizing their training performance. Working across the stack from…
…are seeking a Staff ML/AI Engineer to define and drive the architectural vision for Lyra’s machine learning and generative AI technology landscape…
…improve scalability and efficiency. Build and maintain tools for performance analysis, profiling (e.g., xprof), and debugging of ML models. You have: PhD or…
…More connected assets generate more data, more data trains better models, better models drive more value, and more value wins more assets. The market…
…on TPU architecture and its integration within AI/ML-driven systems. As a Staff CAD Engineer, Silicon Design Environment, you collaborate closely with domain…
…sequential decision making, prediction, generative modeling, foundation/world models, or representation learning. Understanding of the full ML development cycle, from data collection and training…
…performance kernels and features for ML operations, leveraging the Neuron architecture and programming models * Analyze and optimize system-level performance across multiple generations of…
…AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI…
…builder experience through generative AI and foundation models. We're leveraging the latest advances in AI to transform how engineers work from IDE environments…
…the scaling and efficiency of conversational models, including the relationship between data, model size, and real-time performance - Design model architectures informed by hardware…