Sr. ML Architect

- 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
- 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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 its next generation SOC’s for the 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.