Sumanth Lingaraju
About Sumanth Lingaraju
Sumanth Lingaraju is a Technical Engineer currently employed at DealerSocket in Bangalore Urban, Karnataka, India. He has a background in software engineering and holds a Bachelor of Engineering degree in Electronics and Communication from Don Bosco Institute of Technology.
Work at DealerSocket
Sumanth Lingaraju has been employed at DealerSocket since 2021, serving as a Technical Engineer. His role involves applying his technical skills to enhance software solutions within the automotive industry. DealerSocket is known for providing innovative software solutions that improve dealership operations. Sumanth's contributions are focused on leveraging his programming expertise and knowledge of functional safety standards.
Previous Experience at KPIT
Before joining DealerSocket, Sumanth worked as a Software Engineer at KPIT from 2019 to 2021. During his two-year tenure in Bengaluru, Karnataka, he gained valuable experience in software development and engineering practices. His work at KPIT contributed to his understanding of the automotive sector and equipped him with skills relevant to his current position.
Education and Expertise
Sumanth Lingaraju holds a Bachelor of Engineering degree in Electronics and Communication Engineering from Don Bosco Institute of Technology, Bangalore. He completed his studies from 2014 to 2018. His academic background laid the foundation for his expertise in programming languages such as MATLAB Simulink, C, Embedded C, and Python, as well as functional safety and ISO 26262 standards.
Technical Skills and Proficiencies
Sumanth possesses a diverse skill set that includes proficiency in programming languages like MATLAB Simulink, C, Embedded C, and Python. He is experienced in functional safety and ISO 26262 standards, which are essential in the automotive industry. Additionally, he is skilled in using system engineering tools such as IBM Rational Rhapsody and DOORS, and has strong capabilities in data annotation, which is critical for developing machine learning models.