Location
USARate
Years of experience
8About
A Machine Learning Engineer with 8 years of experience in this field. Expertised in computer vision, machine learning, and image processing. Specializing in object recognition, visual search, text detection, and video content analysis, combined with a deep understanding of discriminative learning and deep learning techniques. Proficient in document content analysis, bringing a comprehensive skill set to tackle complex challenges at the intersection of technology and visual data interpretation.Tech Stack
Machine Learning, C++, MATLAB, PythonExperience
- Developed and implemented an innovative text detection algorithm, contributing to a cutting-edge application that extracts textual information from images with remarkable precision, thereby streamlining data extraction processes.
- Successfully integrated deep learning models into multiple projects, optimizing image analysis tasks and achieving higher levels of accuracy in complex visual recognition scenarios.
- Engineered an automated document content analysis pipeline that significantly reduced manual effort and improved data extraction accuracy, providing a robust solution for handling large volumes of textual and visual content.
- Collaborated closely with multidisciplinary teams of data scientists, engineers, and domain experts.
Employment history
As a Senior Software Engineer in the Machine Learning division at Google, I lead the design, development, and deployment of cutting-edge machine learning systems. Collaborating with cross-functional teams, I’m architecting and implementing scalable algorithms, optimizing model performance, and driving innovation in AI technologies.
The lecturer of Applied Machine Learning in the Master of Financial Engineering Program holds a pivotal role in equipping students with the practical skills and theoretical understanding needed to apply machine learning techniques within the financial domain. My responsibilities include designing and delivering engaging lectures and developing hands-on projects.
In this Software Engineering – Machine Learning role, the primary responsibilities included designing, developing, and deploying machine learning models and systems. This involved collaborating with cross-functional teams to understand business requirements, preprocessing and analyzing data, selecting appropriate algorithms, and optimizing model performance.
Managed engineering teams responsible for Conversant’s core technology for text, image and video content analysis and categorization. Collaborated with Product and AdOps teams to define new product features and optimize advertising campaigns. Designed, planed, developed and managed production level machine learning and computer vision systems for image, video and document content analysis. Mentored developers in software design, coding practices, computer vision and machine learning algorithms. Worked closely with the VP of Engineering and other engineering leaders to drive the technical roadmaps.
Designed and developed production level machine learning and computer vision systems. I was responsible for redesigning and rebuilding existing production level computer vision systems to support SET’s first advertising campaigns.
Designed and developed innovative computer vision systems for Houdini/HP Sprout. I did research in object recognition and text detection for Houdini project.
As a Postdoctoral Researcher, I contributed to cutting-edge research projects, building upon my Ph.D. expertise. My responsibilities included designing and conducting experiments, analyzing complex data sets, and developing novel algorithms or methodologies.
My responsibilities included conducting literature reviews, designing and executing experiments, collecting and analyzing data, and collaborating with fellow researchers to brainstorm ideas and troubleshoot challenges. I also played a key role in disseminating findings through presentations at conferences and contributing to research publications.
During my Engineering Internship, I actively participated in various projects and tasks, collaborating with cross-functional teams to gain hands-on experience. I assisted in designing and prototyping new product features, conducted testing and analysis to ensure quality and reliability, and contributed to the optimization of existing processes.
During my engineering internship at Google, I had the opportunity to assist in debugging and troubleshooting issues, contributing to the overall improvement of products and systems at one of the world’s leading technology companies.
As a Junior Specialist, I actively contributed to various projects by assisting with data collection, analysis, and interpretation. My responsibilities included conducting literature reviews, preparing reports, and collaborating with team members to implement solutions.
As a Research Assistant, I conducted experiments, performed simulations, and gathered empirical insights, aiding in the formulation of new hypotheses and the refinement of existing theories.