Arbe is leading a RADAR REVOLUTION, driving a zero-road-fatality reality by enabling truly safe driver-assist systems, and paving the way for a fully autonomous-driving future. The next level of road safety is dependent upon a vehicle’s ability to ‘sense’ the world around it. Arbe’s unparalleled 4D high-resolution imaging radar is disrupting the automotive industry by redefining what’s possible. Join our team of technologists, radar specialists, and scientists to make zero road fatalities a reality, for everyone.
We are looking for a dedicated and experienced Quality & Reliability Engineer (QRE) to join our company specializing in the design of Integrated Circuits (ICs) for the automotive Radar Market. The ideal candidate will have a strong background in reliability engineering within the semiconductor industry, particularly with a focus on automotive applications. This role is critical to ensuring our IC products meet the highest standards of reliability and performance required by the automotive industry.
Responsibilities
Reliability Testing and Analysis:
- Develop and execute comprehensive reliability test plans for IC products, including stress testing, life testing, and failure analysis.
- Perform reliability testing methodologies such as HTOL (High Temperature Operating Life), HAST (Highly Accelerated Stress Test), and ESD (Electrostatic Discharge) testing.
- Analyze reliability data and failure modes to improve product design and manufacturing processes.
- Utilize statistical analysis tools to interpret test data and provide recommendations for reliability improvements.
Product Development Support:
- Work closely with design, process, and test engineering teams to ensure reliability considerations are integrated into product development from the early stages.
- Conduct Design for Reliability (DfR) and Design for Manufacturability (DfM) reviews.
- Participate in FMEA (Failure Modes and Effects Analysis) and other risk assessment activities.
Reliability Standards and Compliance:
- Ensure compliance with automotive industry reliability standards and best practices, including AEC-Q100, ISO 26262, and other relevant standards.
- Develop and maintain reliability metrics and reporting systems to track product performance over time.
- Stay current with industry trends and advancements in reliability engineering methodologies and tools.
Customer Support and Documentation:
- Support customer qualification and validation activities, including PPAP (Production Part Approval Process) submissions.
- Interface with automotive OEMs and Tier 1 suppliers to address reliability concerns and provide technical support.
- Prepare detailed reliability reports and documentation for internal and external stakeholders.
Requirements
- Bachelor’s or Master’s degree in Electrical Engineering, Materials Science, Mechanical Engineering, or a related field.
- Minimum of 5 years of experience in reliability engineering within the semiconductor industry, with an advantage to automotive applications.
- Strong understanding of semiconductor device physics, manufacturing processes, and failure mechanisms.
- Proficiency in reliability testing and analysis tools, including statistical software (e.g., JMP, Minitab).
- Familiarity with automotive reliability standards and best practices (e.g., AEC-Q100, ISO 26262).
- Experience with reliability prediction methods and reliability growth modeling.
- Excellent problem-solving and analytical skills, with a detail-oriented mindset focus on continuous improvement.
- Strong communication and interpersonal skills.
- Ability to work effectively in a cross-functional team environment.
Preferred Qualifications
- Certification in reliability engineering (e.g., CRE).
- Experience with automotive PPAP and APQP processes.
- Familiarity with Six Sigma methodologies and tools.
Yield Analysis:
- Monitor and analyze yield data from production to identify trends, anomalies, and root causes of yield loss.
- Collaborate with process engineering and manufacturing teams to implement yield improvement initiatives.
- Conduct yield enhancement studies and experiments to optimize process parameters and design improvements.
