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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 Machine Learning Engineer – Model Optimization & Quantization”. A match may be a passing mention rather than the job itself. Titles only.
10 roles across 11 listings · show every listing
…Experience with machine learning infrastructure, C++, performance, GPU programming, mobile GPU. Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a…
…deep generative models, Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning, unsupervised learning, and graph NNs. Drives systems innovations for model efficiency advancement…
…Decisioning & optimization: causal inference, policy optimization, constrained optimization, or reinforcement learning. Training & inference efficiency: model sparsification, quantization, distillation, or parallelism and partitioning design. - Communication…
Meta is seeking a Staff Software Engineer to join the Core Machine Learning team, focused on building and scaling the foundational ML infrastructure and…
…About the role As a Senior Staff Machine Learning Scientist, you own the inference and optimization layer that makes AI in agentic workflows fast…
…You will join a team of world-class machine learning engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our customers…
…and systems engineering activities. Job responsibilities include: Implement sensor signal processing and machine learning algorithms across various embedded SOCs. Debug, verify, optimize, and tune…
…As a Machine Learning and System Optimization Engineer, you will orchestrate and allocate overall system capacity to various core perception models running on-bot…
…Machine Learning, Robotics, or a related field. 5+ years of experience with deep learning architectures (especially Transformers, Diffusion Models, MoEs), algorithms, and optimization techniques…
…large-scale data engineering, hardware-savvy optimizations, and reproducible experimentation—researchers can produce impactful, trustworthy advancements in foundational deep learning. FOUNDATIONAL PAPERS This job…