Analog Circuit Design Engineer - AI/ML methodology

Qualifications

• Minimum requirements:
• Bachelor's in Electrical Engineering, Computer Engineering, Electrical and Computer Engineering, or a related field
• 2 to 5 years experience
• Cumulative 3.0/4.0 GPA or higher
• Preferred qualifications:
• Strong fundamentals in analog circuit design concepts with relevant coursework and design projects
• Course project or internship experience in the design, simulation, and layout of one or more analog IPs, such as band-gap reference, ADC, DAC, amplifier, oscillator, comparator, IO cells, and power-management blocks like LDO and DCDC.
• Familiarity with corners, statistical analysis, and post-layout concepts is a plus.
• Working knowledge of Cadence Virtuoso ADE, including Maestro and SPECTRE simulator
• Foundational proficiency in Python and one or more packages such as Pandas, PyTorch, TensorFlow, scikit-learn, and Matplotlib
• Foundational knowledge of machine learning concepts such as Neural Networks, Graphs, Clustering and Regression techniques, and Decision Trees
• Strong verbal and written communication skills
• Demonstrated analytical and problem-solving skills, especially in new domains
• Ability to work in teams across time zones and collaborate effectively with people in different functions
• Ability to take initiative and drive for results in a timely manner
• Minimum requirements: - Bachelor's in Electrical Engineering, Computer Engineering, Electrical and Computer Engineering, or a related field - 2 to 5 years experience - Cumulative 3.0/4.0 GPA or higher Preferred qualifications: - Strong fundamentals in analog circuit design concepts with relevant coursework and design projects - Course project or internship experience in the design, simulation, and layout of one or more analog IPs, such as band-gap reference, ADC, DAC, amplifier, oscillator, comparator, IO cells, and power-management blocks like LDO and DCDC. - Familiarity with corners, statistical analysis, and post-layout concepts is a plus. - Working knowledge of Cadence Virtuoso ADE, including Maestro and SPECTRE simulator - Foundational proficiency in Python and one or more packages such as Pandas, PyTorch, TensorFlow, scikit-learn, and Matplotlib - Foundational knowledge of machine learning concepts such as Neural Networks, Graphs, Clustering and Regression techniques, and Decision Trees - Strong verbal and written communication skills - Demonstrated analytical and problem-solving skills, especially in new domains - Ability to work in teams across time zones and collaborate effectively with people in different functions - Ability to take initiative and drive for results in a timely manner