Sr Deep Learning Verification Engineer

Job Details: Job Description: The Role and Impact As a Sr Deep Learning Hardware Verification Engineer, you will play a pivotal role in shaping the future of AI hardware by validating and optimizing next-generation NPU silicon solutions. In this role you will join the NPU Hardware Pre-Silicon Validation team working closely with design engineers, model engineers and AI architects to validate components of the next generation NPU IP portfolio, your contributions will directly shape Intel's advancements in AI technologies. Your responsibilities will include: • Functional Verification of complex digital design block(s) on the latest generations of Intel's NPU AI accelerators. • Architect, development and implementation of verification environments from initial planning through the validation lifecycle to review and signoff. • Development of test plans and test cases. • Implementation of random test generators, high level transactional models, bus functional models (BFMs), functional/formal constraints, checkers and scoreboards, coverpoints/covergroups and SVA properties. • Implementation of software based testcases for functional and performance based testing of the NPU AI accelerators. • Collaborate with cross-functional teams to analyses and address next-generation AI requirements, influencing the AI product roadmap. Leixlip is the primary location for this position, however, we offer some flexibility to support your work/life balance arrangements.

The compensation range displayed in this posting reflects the minimum and maximum target compensation for this position. Within this range, individual pay is determined by job related skills, experience, and relevant education, training. As part of our total compensation approach, the final offer may include additional pay components and benefits. Your recruiting team will share the confirmed base salary along with any applicable total compensation elements upon employment offer delivery. Work Model for this Role This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change. *