Top Senior Level QA Engineer Jobs

The Senior Software Test & Automation Engineer designs, develops, and executes test software solutions for WiFi SOC and radio debug and automated test solutions specifically for the IoT market. Responsibilities include collaborating with various teams, developing test cases and documentation, and creating debug tools, ensuring high-quality outputs and effective communication within multi-functional teams.

The Principal Engineer will lead the development of integrated custom analog and mixed signal IPs, focusing on high-performance ADC design. Responsibilities include supervising design teams, conducting layout activities, performing simulations, and collaborating with cross-functional engineers to meet product specifications and ensure quality.

As a PHY Verification Engineer/Lead at InnoPhase IoT, you will define and develop UVM testbenches for wireless PHY and MAC layers, collaborating with design and system engineers. Responsibilities include optimizing test plans, conducting verification coverage analysis, running regressions, and refining verification tools. Your role also involves debugging and problem-solving in a team environment.

The Site Reliability Engineer (SRE) will enhance observability, create dashboards, set up alerts, manage on-call rotations, and improve the reliability of deployment processes. This role requires expertise in monitoring and deployment technologies, as well as proficiency in a primary programming language.

As a Staff Engineer in DRAM, you will develop and optimize DRAM architecture, lead design specifications, conduct performance analysis, and collaborate with cross-functional teams. You will also work on power consumption reduction methods while interacting with internal and external customers.

The Staff Engineer will oversee DRAM Customer Quality by managing product quality and reliability issues, coordinating failure analysis, communicating with Tier 1 customers, and ensuring compliance with quality requirements. The role involves collaboration with engineering teams and the creation of reports to track technical issues.

The role involves collaborating with hardware and software engineers to optimize AI/ML workloads, troubleshoot issues, analyze performance bottlenecks, and contribute to innovative hardware solutions. Candidates will research ML trends and develop scalable systems to enhance performance and efficiency.