# Karan Patel > Experienced Backend Developer | Expert in Python, Go & JavaScript | Specializing in API Development and Microservices | Proficient in Docker, Kubernetes, and GCP Deployment Location: San Francisco Bay Area, United States Profile: https://flows.cv/karanpatel Dedicated Software Engineer with extensive experience in programming, framework development, deployment, and database management. Proficient in Python, Go, JavaScript, and a suite of modern technologies. Passionate about developing scalable applications and optimizing system performance through innovative solutions. ## Work Experience ### Software Engineer @ Selector Jan 2022 – Present | Santa Clara, California, United States Spearheaded the design, development, and testing of key backend services, primarily using Python and Go, with a strategic focus on converting certain services from Python to Go for optimized performance. This initiative included building robust APIs for effective service interaction and streamlined data storage in databases. Additionally, I crafted APIs utilizing FastAPI in a microservice architecture to enhance scalability. The entire suite of services was efficiently deployed using Docker and Kubernetes on the Google Cloud Platform (GCP), ensuring robustness and scalability in the operational environment. ### Back-end Developer @ Taboola Jan 2021 – Jan 2021 | Los Angeles, California, United States Contributed to the development of the Newsroom product by creating APIs that provide in-depth analysis of Click-through rates across various timelines. My role encompassed the development and rigorous testing of APIs dedicated to data storage in HBase. This process was enhanced through the utilization of Apache Spark for data aggregation and Apache Kafka for efficient data queuing, ensuring seamless data flow and integrity. ### Software Developer @ Big Analytixs Jan 2021 – Jan 2021 | San Jose, California, United States Engineered and implemented a sophisticated automated ETL (Extract, Transform, Load) pipeline, designed to refine data for enhanced analysis and predictive modeling. Successfully deployed this comprehensive pipeline on Azure, leveraging the aztk Python library to fully automate the data processing workflow, ensuring efficiency and reliability in data handling. ### Graduate Teaching Assistant @ San Jose State University Jan 2020 – Jan 2021 | San Jose, California, United States As a Teaching Assistant for DATA 255 - Deep Learning Technologies in the Data Science Department, I played a crucial role in collaborating with the professor to design the course curriculum, ensuring it met educational standards and objectives. Additionally, I was responsible for the assessment and grading of student assignments and exam papers, contributing significantly to maintaining the academic rigor and quality of the course. ### Graduate Teaching Associate @ San Jose State University Jan 2020 – Jan 2021 | San Jose, California, United States As a Teaching Associate for ME 30 - Computer Applications in the Mechanical Engineering Department, I specialized in instructing students on the fundamentals of Python programming. This included practical applications, notably implementing code on the Circuit Playground Express by Adafruit, thereby bridging the gap between theoretical knowledge and real-world technical skills. ### Software Engineer @ EZDI, Inc - an AGS Health company Jan 2018 – Jan 2019 | Ahmedabad, Gujarat, India Developed an innovative end-to-end learning model by synergistically combining BI-LSTM (Bidirectional Long Short-Term Memory) and CRF (Conditional Random Field) algorithms. This advanced integration yielded a notable 2% increase in precision over traditional statistical algorithms, marking a significant enhancement in the model's performance and accuracy. ### Software Engineer @ EZDI, Inc - an AGS Health company Jan 2017 – Jan 2018 | Ahmedabad Area, India Conducted a comprehensive analysis of the stacking method through the integration of various classifiers, and benchmarked its performance against bagging and boosting algorithms. This approach not only enhanced the model's accuracy by 5% but also significantly reduced training time when compared to conventional Neural Network methodologies. ## Education ### Master's degree in Software Engineering San José State University ### Bachelor of Technology - BTech in Information Communication Technology Ahmedabad University ## Contact & Social - LinkedIn: https://linkedin.com/in/karanpatel5115 - Portfolio: https://kp5115.github.io/ --- Source: https://flows.cv/karanpatel JSON Resume: https://flows.cv/karanpatel/resume.json Last updated: 2026-03-29