Machine Learning Engineers....WHERE ARE YOU? We have a new System on a Chip (SoC) client seeking a Machine Learning Engineer to develop algorithms for their ground breaking SOC. This is a HYBRID role in Southern California. Please view the following link for the role: Machine Learning Engineer https://lnkd.in/gQXbnT93 #Hardwareengineering #embeddedengineer #startup #AI #ML #machinelearning #systemonachip #tensorflow #RTOS #diversity #womeninengineering #hiring
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Get in touch! ML System Performance Engineer, £80,000-£120,000 DOE, hybrid working, bonus scheme & more! - #Cambridgeshire. To find out more, please visit the link below #MachineLearning #ArtificialIntelligence #Software #ICResources #DataEngineering #Robotics #3DReconstruction #DeepLearning #Graphics #ImageProcessing #TechnologyRecruitment #NLP #TechnologyJobs #DataScience #TechnologyCareers #AI #ComputerVision
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Deep Learning Engineer - LLMs and Diffusion Models I am #hiring now #Deep #Learning #Engineers and #Researchers to work on #GenerativeAI (#LLMs and #Diffusion #Models). #Visiting #professors are welcome too. You will work on one of these topics: - create new hashtag #DL #architectures to make LLMs/Diffusion Models more hashtag #efficient at #inference and #training , e.g., KVCache compression, pruning, distillation, conditional computation- make #DL #training (LLM and beyond) more efficient and resilient, e.g., distributed checkpointing for a #super #large-#scale LLM training. Job req: https://lnkd.in/dfcdXSSJ Our recent works on these topics: - Dynamic Memory Compression paper from ICML'24: https://lnkd.in/dDwbQk5z - Fast distributed checkpointing for better training resiliency: https://lnkd.in/d6S498ng - Pruning and Distillation in LLMs: https://lnkd.in/dFNsZuNZ Our team is based in Poland and Switzerland (remote work + access to nice offices). We collaborate a lot with other NVidia Research Teams in US. Exiting times ahead. Please join us on this journey!
I am #hiring now #Deep #Learning #Engineers and #Researchers to work on #GenerativeAI (#LLMs and #Diffusion #Models). #Visiting #professors are welcome too. You will work on one of these topics: - create new #DL #architectures to make LLMs/Diffusion Models more #efficient at #inference and #training , e.g., KVCache compression, pruning, distillation, conditional computation - make #DL #training (LLM and beyond) more efficient and resilient, e.g., distributed checkpointing for a #super #large-#scale LLM training. Job req: https://lnkd.in/dfcdXSSJ Our recent works on these topics: - Dynamic Memory Compression paper from ICML'24: https://lnkd.in/dDwbQk5z - Fast distributed checkpointing for better training resiliency: https://lnkd.in/d6S498ng - Pruning and Distillation in LLMs: https://lnkd.in/dFNsZuNZ Our team is based in Poland and Switzerland (remote work + access to nice offices). We collaborate a lot with other NVidia Research Teams in US. Exiting times ahead. Please join us on this journey!
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[Q] What's good about the deep learning research team at Picovoice? [A] We are doing things differently so we don't have to train the same architecture on many H100s while praying that we can magically beat companies doing the same thing with more GPUs. [i.e., we have a real chance of success.] [Q] What's bad about the deep learning research team at Picovoice? [A] We are doing things differently so we don't have to train the same architecture on many H100s while praying that we can magically beat companies doing the same thing with more GPUs. [i.e., we are tackling hard problems with no existing solutions.] BTW we are hiring for three roles within the team https://lnkd.in/ehq_UaJ6 https://lnkd.in/e87CFqJb https://lnkd.in/eh82KAyB Happy Friday, everyone! #hiring #deeplearning #llm #voiceai
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I am #hiring now #Deep #Learning #Engineers and #Researchers to work on #GenerativeAI (#LLMs and #Diffusion #Models). #Visiting #professors are welcome too. You will work on one of these topics: - create new #DL #architectures to make LLMs/Diffusion Models more #efficient at #inference and #training , e.g., KVCache compression, pruning, distillation, conditional computation - make #DL #training (LLM and beyond) more efficient and resilient, e.g., distributed checkpointing for a #super #large-#scale LLM training. Job req: https://lnkd.in/dfcdXSSJ Our recent works on these topics: - Dynamic Memory Compression paper from ICML'24: https://lnkd.in/dDwbQk5z - Fast distributed checkpointing for better training resiliency: https://lnkd.in/d6S498ng - Pruning and Distillation in LLMs: https://lnkd.in/dFNsZuNZ Our team is based in Poland and Switzerland (remote work + access to nice offices). We collaborate a lot with other NVidia Research Teams in US. Exiting times ahead. Please join us on this journey!
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Must have conference for developers, get to know a bit more about what AI can do for you on the dev side.
Looking for your next challenge as a Senior Software Engineer, Deep Learning Inference? Check out this amazing career opportunity by NVIDIA! https://lnkd.in/dVa9_bZv See more jobs at www.aidevtlv.com/jobs
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🚀 Looking to build highly performant and scalable ML ecosystems leveraging the latest HPC architecture and technologies? We’re currently representing exceptional professionals ready to make an impact: 🔹 AI HPC SRE (HPC & Infiniband): - Introduced Infiniband Island for MPI apps. - Achieved 30% power savings via power management strategies. - Designed and deployed HPC as a service from scratch. 🔹 AI Hardware Engineer: - Developed neural network SDKs for AI accelerators. - Led AI inference software development and ONNX ecosystem transitions. - Pioneered FPGA-based runtime co-designs. 🔹 AI Compiler Engineer: - Built a custom compiler optimizing Apache Spark queries. - Added advanced features like fixed-point arithmetic and HyperLogLog. - Created a personal LLVM backend for a custom instruction set. 👉 Interested in innovative AI solutions? Connect to explore how they’re shaping the future of tech! Like, share, comment, or message for more! 💪 #Hiring #AI #HPC
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Get in touch! Machine Learning Research Engineer, System Infrastructure - #Midlothian. Interested? Click the link to apply #TechnologyRecruitment #3DReconstruction #Graphics #MachineLearning #NLP #DataEngineering #DataScience #Software #ImageProcessing #AI #TechnologyJobs #Robotics #ICResources #TechnologyCareers #DeepLearning #ArtificialIntelligence #ComputerVision
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🚀 Prometheux can also prevent LLM factual hallucinations and validate responses. 🔍 Pure LLMs are inherently probabilistic and can produce plausible yet inaccurate outputs that hinder trustworthiness. 🧑🔬 Prometheux turns an LLM response into an accurate, verifiable virtual knowledge graph and our customers can configure policies to be executed over it using logic-based reasoning, validating it and providing a mathematically sound explanation of its correctness/incorrectness. 💡 Because Prometheux performs highly optimised data processing, it can validate billions of facts, free from context window limitations. Know someone we should connect with? We are also hiring software engineers! #knowledgegraphs #AI #neurosymbolic #LLMs #validation
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EDITED TO ADD: to be CRYSTAL CLEAR about professionalism in the face of last weeks' news, I learned of these reqs before I had any information (only vague rumors) about what was going on at Intel. So to be safe I added "too early to start circling" below deliberately so there would be no question of poaching or kicking a company when they're down. I have enough investment (in decades of my life and undiversified stock) to wish Intel any ill will at all, and I mostly loathe schadenfreude in principle. Meena Arunachalam's original post about these reqs was made *several weeks ago.* #togetherweadvance is AMD's slogan, but as tech workers, I personally would apply it in this case individually and as a group to my colleagues throughout the industry. ---- [Original post] ------------------- It's too early for vultures to start circling my old #intel colleagues, but if you're interested in #AI, you might consider some of the opportunities with my colleague at #AMD wherever you are working now. This company is going places in AI. #togetherweadvance
Fellow, AI Systems Design Engineering | AI performance and systems| Data center GPUs | Build high performing and cross-organizational teams
We have some exciting opportunities in AI Software innovation. Come join my fast-paced team and work on developing software and technologies to create performant cutting-edge Gen AI models and workloads on Data center GPUs. AI Software Architect: https://lnkd.in/g-VXYenU AI Software Development Engineer: https://lnkd.in/gyvwjJrf AI Software Engineer: https://lnkd.in/gY_B2GtS
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