Job Details:
Job Description:
We are seeking a highly skilled and experienced Verification Team Leader to join us and lead the Cache verification team and play a major role in ensuring the quality and functionality of our cutting-edge products for the AI industry. Habana Group, within Intel.
This position is ideal for someone with a strong technical expertise and analytical skills, a passion for verification methodologies, who is also a natural leader.
Responsibilities:
- Manage a team of verification engineers of various qualities and experience characteristics.
- Lead the development and implementation of comprehensive verification plans and strategies for complex hardware designs, ensuring alignment with industry best practices.
- Oversee the maintenance of verification environments using advanced industry-standard tools and methodologies, mentoring junior engineers in the process.
- Review test cases to verify design functionality and compliance with specifications.
- Collaborate closely with design, architecture, and firmware engineers to deeply understand specifications, proactively identifying and addressing potential design flaws during the development process.
- Analyze verification results, derive insights, and effectively communicate findings and recommendations to stakeholders, contributing to strategic decision-making and project direction.
Qualifications:
- B.Sc. in Electrical or Computer Engineering.
- 10+ years of proven experience in VLSI chip Verification engineering, with a focus on high-end SoCs and AI applications.
- 4+ years of leadership experience in verification projects.
- 3+ years of proven experience in verifying cache systems – an advantage.
- Proven track record of leading verification activities and delivering successful projects that meet demanding quality and performance targets.
- Excellent analytical and communication skills, with the ability to effectively collaborate with cross-functional teams in a fast-paced environment.
- Strong motivating and mentorship skills to guide and inspire team members towards achieving exceptional performance.
- Strong proficiency in SystemVerilog, UVM, and other verification tools.
- Experience with AI-specific performance benchmarks, NoC performance benchmark and optimization techniques – an advantage.
- Knowledge of system-level scenario analysis and modelling for high-performance SoCs – an advantage.
- Experience with scripting languages (e.g., Python, Perl) for automation and data analysis – an advantage.
This position is expected to change location in the near future to the Petah Tikva campus.
Job Type:
Experienced Hire
Shift:
Shift 1 (Israel)
Primary Location:
Israel, Petah-Tikva
Additional Locations:
Business group:
As a member of the Chief Technology Office, Artificial Intelligence, and Network and Edge Group (CTO AI NEX), you will be committed to strategically penetrating the AI market by delivering disruptive and transformative solutions. Your focus will be on leveraging technology innovation and incubation to drive commercial success, ensuring that advancements create significant value. The team is dedicated to driving the software-defined transformation of the world's networks profitably, setting new standards for efficiency and connectivity. Through these priorities, you aim to lead the way in technological evolution and redefine the future of global networks.
Posting Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Position of Trust
N/A
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.
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