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The team is made up of machine learning researchers and engineers, who support and innovate production recommendation models and drive product impact. - Good communication and teamwork skills, be passionate about learning new techniques and taking on challenging problems.
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Our team provides solutions to empower machine learning development in Nuro and optimize on-cloud training and onboard inference. Knowledge in using at least one deep learning framework, e.g. Tensorflow, Pytorch, JAX. Be able to understand deep learning algorithms, e.g. computer vision, NLP, behavior planning.
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Team members are engaged in the design and optimization of low level computational support for all aspects of machine learning and computational primitives in service of models such as Text to Speech, Voice Isolation, Apple Music Sing to mention a few.
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And machine learning including Deep Learning frameworks like TensorFlow/PyTorch. You have at least 1-3 years of hands-on experience in one or more of the following areas: Autonomous Driving (preferable), Robotics, or Deep Learning in general.
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5 years of experience with machine learning frameworks (e.g. Pytorch, TensorFlow), artificial intelligence, deep learning or natural language processing. 3 years of experience with machine learning algorithms and tools (e.g. Pytorch, TensorFlow), artificial intelligence, deep learning or natural language processing.
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Years of experience in Databricks Machine Learning • Have you deployed any models using Databricks model serving • Have you deployed a model with unstructured data using Databricks model serving.
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Deep knowledge of Autonomous Driving Behavior includingVarious formats of maps (rasterized, vectorized) Diffusion modeling: different forms of guidance, sampling optimization, probability estimation Transformer Decoding Flow-based, VAE, and RNN-based generative approaches Prediction vs Planning Marginal vs Conditional vs Joint Open vs Closed loop Imitation Learning approaches.
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Coactive was founded by experts who shaped the fields of high-performance deep learning and data-centric AI. We have the scars from building and working with the first generation of modern machine learning systems at Google, Meta, Pinterest, eBay, Lyft, and other leading organizations.
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Strong coding and debugging skills, and demonstrated expertise in one or more of the following areas: Machine Learning, Deep Learning, Slurm, Docker/Kubernetes, Kubernetes, Singularity, MPI, MLOps, LLMOps, Ansible, Terraform, and other high-performance AI cluster solutions.
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MS or Ph. D. in Computer Science, Software Engineer, Data Science, Machine Learning, Statistics, Operations Research or related field. Develop machine learning solutions using Python and its associated ecosystem.
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Specialized experience in one or more of the following machine learning/deep learning domains: Model compression, hardware aware model optimizations, hardware accelerators architecture, GPU architecture, machine learning compilers, or ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine learning frameworks (e.g. PyTorch), numerics and SW/HW co-design.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Building machine learning models and systems, interpret their output, and communicate their results to internal/client teams and how those outcomes realize business value.
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Experience with solving and using machine learning for real-world problems involving scientific/engineering simulations (domains/applications - industrial, life sciences, high energy physics, earth sciences – seismic, weather & climate modeling; physics types - CFD, structural, electromagnetics, optics, acoustics etc.
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Meta is seeking a Postdoctoral Researcher to join Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as Natural Language Processing, Multimodality, Artificial Intelligence and Machine Learning.
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More specifically, you will provide thought leadership on and lead strategic efforts in Computer Vision (CV) and Machine Learning (ML) areas for Ring and Blink, covering themes including but not limited to 3D vision, SLAM, Classic Deep Learning, and Generative AI, and work with Product, Science, and Engineering teams to deliver short- and long-term CV/ML solutions in production for optimized edge-based solutions to large-scale models.
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machine learning jobs Company: Raising in Sunnyvale, CA
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