# Tejas Mahajan > Software Engineer at Nimble Robotics | Applied ML | Data Platforms | NYU Courant CDS | Location: San Francisco Bay Area, United States Profile: https://flows.cv/tejasmahajan I am currently working as a Software Engineer in the Data/Infrastructure Team at Nimble Robotics. I have a Masters in Computer Science at Courant Institute of Mathematical Sciences, New York University (NYU) and open to opportunities related to Machine Learning Engineer / Perception Engineer / Data Scientist / Software Engineering. I have previously worked as a data scientist and machine learning engineer in the fintech, regtech, fashion and robotics domain, through my work at Karza(fintech (acquired)), Marsplay(fashion (acquired)) and Zipline (robotics). I have developed and deployed scalable algorithms on the AWS and Google Cloud Stack. My work primarily involved reading and implementing ideas from various research papers, creating the first solution and then iteratively improving it depending on compute and product requirements. ## Work Experience ### Software Engineer @ Nimble Jan 2026 – Present | San Francisco, CA ### Software Engineer (Data Team) @ MerQube Jan 2023 – Jan 2026 | San Francisco Bay Area MerQube is an innovative fintech firm, leading the development of cutting edge technology for indexing and rules-based investing. MerQube designs and calculates a wide variety of indices, ranging from thematic to ESG, factor and retirement, while covering multi-asset, equities, futures as well as options. Few highlights of my role here are: - Engineered the migration of equity reference and end-of-day pricing pipelines to a new provider platform, ensuring uninterrupted data delivery for index calculations with zero downtime. - Led the development of a scalable options data platform, defining the data model, building ingestion and monitoring systems, and partnering with product, data providers, and financial engineers to resolve complex data integrity challenges. Delivered a unified data access layer that powers multi-asset index development and self-service analytics across teams. - Transformed operations workflow by developing automated validation checks for end-of-day prices and corporate action data across multiple providers. Enhanced data accuracy and consistency with customizable override capabilities. ### Graduate Teaching Assistant @ NYU Center for Data Science Jan 2022 – Jan 2023 | New York City Metropolitan Area Fall 2022 and Spring 2023 - Deep Learning by Prof. Alfredo Canziani & Yann Lecun. ### Perception Software Engineer Intern @ Zipline Jan 2022 – Jan 2022 | San Francisco Bay Area Zipline designs, manufactures and operates the world’s largest autonomous drone delivery network, enabling on-demand logistics of essentials, from medical supplies to consumer goods, at unprecedented speed and scale. Few highlights of my role here were: - Building perception software as part of the acoustic detect and avoid team to answer a specific question, How to tune the current encounter detection models to be resilient to changes in sensor environment, in order to decrease the false positive rate. - Analysed flight data at production nests, to find spatial and temporal correlation for locating probable sources of false positives. - Fine tuned intruder detection models using hard negative samples to reduce false positives by 70% on production nests while having minimal impact on sensitivity. ### Data Scientist @ Karza Technologies Jan 2018 – Jan 2020 | Mumbai, Maharashtra, India Karza Technologies (Now Acquired by Perfios) was a data, analytics, automation, and decisioning solution provider to FIs, catering to the entire lending lifecycle from onboarding to diligence & monitoring to collections. Karza Technologies solutions enable systemic fraud prevention, risk management, compliance & automation through superior data engineering and deep tech applications. Few highlights of my role at Karza were: - Developed an end to end OCR Pipeline for the KYC Documents by implementing a robust synthetic data generation pipeline, model validation, hypothesis testing and training modules for text recognition, card detection and text detection tasks. - Light weight reformulation of fixed length text recognition model using the CTC framework and TensorRT for weight quantization to decrease model size by 85\% while maintaining almost the same accuracy level, so that it could be deployed as AWS Lambda service. - Progressively optimized the OCR task specific models bridging the latency vs task specific evaluation metric tradeoff (like word and character accuracy for text recognition). ### Machine Learning Intern @ Marsplay Jan 2018 – Jan 2018 Marsplay (acquired) built a social commerce platform that turned creator-driven content into shoppable experiences, helping users discover and buy products endorsed by people they trust. Few highlights of my role here were: - Conceptualized and curated a rich dataset for garments and footwear detection and implemented a multi-level deep neural network to accurately predict the garment type and its related attributes. - Augmented search retrieval information by extracting the color of detected object and mapping it to its appropriate shade name. - Improved click through rate and user engagement time by leveraging the metadata of detected objects for better search and visual interaction elements. - Deployed the models by developing APIs using Flask; packaging them into containerized applications and deploying as serverless endpoints on Google Cloud Run improving the click through rate and user engagement time. ### Intern @ IBM Jan 2018 – Jan 2018 | Pune Area, India • Developed a proof of concept for Personal Identifiable Information data classification system with focus on detecting and redacting social security cards in images and car number plates in videos for data in storage systems to be GDPR compliant. • Implemented a suite of image processing functions using python to develop a synthetic dataset of social security cards and cars number plates. • Designed and optimized a deep neural network object detector using tensorflow for detecting the PII data along with implementing fuzzy logic to redact it. ## Education ### Master of Science - MS in Computer Science New York University ### Bachelor of Engineering (BE) in Computer Science Maharashtra Institute of Technology ### Deep Learning Nanodegree in Deep Learning Udacity ### Artificial Intelligence Nanodegree in Artificial Intelligence Udacity ## Contact & Social - LinkedIn: https://linkedin.com/in/tejas-mahajan-21175a118 --- Source: https://flows.cv/tejasmahajan JSON Resume: https://flows.cv/tejasmahajan/resume.json Last updated: 2026-03-29