Evi Technologies Limited
Technology
AppliedScientist,HardwareDevicesScienceTeam
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Applied Scientist, Hardware Devices Science Team at Evi Technologies Limited. Skills: Gen AI, Edge AI, Model optimization, Hardware-ML co-design. Engage in research. Contribute to training platform”
What You'll Achieve.
Develop next generation edge models; Optimize models for custom ML HW; Train custom Gen AI models that beat SOTA; Pave path for developing production models
Industry & Context.
Derive research approaches from first principles
What They're Looking For.
Must Have
PhD in quantitative field, Experience applying theoretical models, Experience in deep learning models architecture design, Experience in deep learning training and optimization, Experience in model pruning, Experience implementing algorithms using toolkits, Experience implementing algorithms using self-developed code, Experience with Python, Experience with Java, Experience with C++
Nice to Have
PhD in quantitative science field, Experience designing novel algorithms via optimization theory, Experience designing novel algorithms via constrained optimization, Experience with reinforcement learning applications, Experience with training of diffusion models, Experience with mixture-of-experts models, Experience with implementation of novel ML algorithms in distributed settings, Experience in professional software development, Experience building machine learning models, Experience developing algorithms for business application
What You'll Do.
Contribute to training platform
Invent optimization techniques
Derive research approaches
Create theoretical specifications
Justify correctness of ideas
Train custom Gen AI models
Collaborate with compiler engineers
Collaborate with Applied Scientists
Collaborate with Hardware Architects
Collaborate with product teams
Publish in open source
Present at ML conferences
How You'll Work.
Team & Collaboration
Compiler engineers; Applied Scientists; Hardware Architects; Product teams
Full Job Description
Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities What will you do? - Engage in state-of-the-art and innovative research in areas such as Gen AI, model compression, and knowledge distillation - Contribute to a novel and comprehensive training platform custom-tailored for preparing models for edge applications - Invent optimization techniques to push the boundaries of deep learning model training - Derive research approaches from first principles via knowledge of Information Theory, Statistics, Scientific Computing, and Deep Learning Theory - Create and propose detailed theoretical specifications for novel research ideas and directions, and rigorously justify their correctness - Train custom Gen AI models that beat the SOTA and paves path for developing production models - Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices by cohesively unifying software and hardware - Publish in open source and present on Amazon's behalf at key ML conferences - e.g. NeurIPS, ICLR, MLSys Preferred Qualifications: - PhD in quantitative science field, e.g. Applied Mathematics, Statistics, Physics - Experience with designing novel algorithms via optimization theory and constrained optimization - Experience with applications of reinforcement learning to Gen AI model training - Experience wit
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