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The Product Engineer position is in the Software and Acceleration Products group, located in San Jose (California) or Longmont (Colorado). The successful candidate will focus on the AI engines part of Versal ACAP tools roadmap definition, feature specification, validation, documentation, tutorials and train-the-trainer material. The candidate will work in a highly cross-functional R&D environment, interacting with HW and SW engineering teams, internal acceleration application teams and tier-1&2 customers to enable high performance machine learning (CNN/DNN), DSP processing (Wireless 5G) and vector-based designs, with good Ease-of-Use and solid methodologies.
- Drive successful adoption of Xilinx AI Engine tool flows by working closely with key customers, Xilinx Marketing and field specialists
- Drive updated design methodologies around the AI Engines usage, based on industry's best practice and existing Xilinx methodologies
- Triage tools, flows and methodology issues to refine compilation tools features for each release and provide short term solutions to keep users and customers on track with their projects
- Explore software and hardware compilation algorithms, memory architecture and function mapping to Versal ACAP devices to optimize metrics such as throughput, latency, performance per watt.
- Work closely with design and compilation teams to create micro-architecture specifications along with special tool support to gradually improve market specific applications.
- Deep-dive on new and critical tool issues seen by customers to identify work arounds. Triaging reported issues in the implementation for tool enhancements.
- Actively explore innovative methodologies and design practices with emphasis on high level design languages (C/C++) and their impact on tool chain flow from design entry to generating boot image.
- Tracking product development schedules and issues, and validating the readiness of new or enhanced features in any new Vivado release.
- Develop and deliver training materials on new features and methodologies.
- Authoring high quality documentation tuned to the needs of the reader for their areas of expertise.
- Staying current with industry trends, algorithms, and practices.
M.S. in Electrical Engineering, Computer Science, Computer Engineering (or a closely related field of study) with minimum 3 years of relevant experience.
- 2+ years hands on experience of CPU, GPU or VLIW architectures, programming models and tool flows
- Strong knowledge of C/C++ for high performance computing, debugging and methodology
- Proficient in Python, basic knowledge of Tcl and Perl
- Experience with HW pipeline and micro-architecture design of machine learning algorithms is a plus
- Experience in FPGA design flow, RTL design or HLS-based design is a plus
- Experience with deep learning frameworks (Tensorflow, Keras, PyTorch, Caffe, CNTF) is a plus
- Has good understanding of software-vs-hardware trade-offs to help users adopting best practice and achieving high quality results
- Can resolve customer escalations professionally in a quick and effective manner
- Ability to handle and solve complex system level issues
- Can simplify and communicate even the most complex subjects, making options, tradeoffs, and impact clear