Amazon
Sr. ML Architect
Amazon, Sunnyvale, California, United States, 94087
Job ID: 2590992 | Amazon.com Services LLC
Amazon Devices is an inventive research and development company that designs and engineers 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 its next generation SOC’s for machine learning enabled consumer products. We are looking for exceptional engineers to join the SOC development team and help develop the next generation of chips based on a revolutionary architecture. Work hard. Have Fun. Make History.
Key job responsibilities
What will you do? Analyze deep learning workloads and map them to Amazon’s Neural Edge Engine Propose and implement new hardware architectures or improvements to our existing ones, that enable future ML workloads to run efficiently on our accelerator Collaborate closely with compiler engineers, model developers, hardware architects, and product teams to build the best ML-centric hardware and software solutions for our devices Deliver hardware architecture, microarchitecture, and other design collateral for our next generation ML accelerators Build tools for modeling and performance evaluation to enable power, performance, cost options, and trade-offs Work with full stack silicon designers to realize the architecture on silicon. BASIC QUALIFICATIONS
- Experience with neural deep learning methods and machine learning - 3+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - PhD, or Master's degree and 6+ years of applied research experience - 3+ years of designing HW IP preferably for machine learning workloads PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - Experience programming in HDL like Verilog, VHDL or HLS (High Level Synthesis) Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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What will you do? Analyze deep learning workloads and map them to Amazon’s Neural Edge Engine Propose and implement new hardware architectures or improvements to our existing ones, that enable future ML workloads to run efficiently on our accelerator Collaborate closely with compiler engineers, model developers, hardware architects, and product teams to build the best ML-centric hardware and software solutions for our devices Deliver hardware architecture, microarchitecture, and other design collateral for our next generation ML accelerators Build tools for modeling and performance evaluation to enable power, performance, cost options, and trade-offs Work with full stack silicon designers to realize the architecture on silicon. BASIC QUALIFICATIONS
- Experience with neural deep learning methods and machine learning - 3+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - PhD, or Master's degree and 6+ years of applied research experience - 3+ years of designing HW IP preferably for machine learning workloads PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - Experience programming in HDL like Verilog, VHDL or HLS (High Level Synthesis) Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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