Vikas Patidar

Software Engineer

San Francisco, California, United States7 yrs 9 mos experience
Most Likely To SwitchAI ML Practitioner

Key Highlights

  • Expert in Machine Learning and Deep Learning technologies.
  • Proven track record in developing innovative software solutions.
  • Strong background in data science and recommendation systems.
Stackforce AI infers this person is a SaaS-focused software engineer with expertise in machine learning and data science.

Contact

Skills

Core Skills

Deep LearningComputer VisionMachine LearningSoftware DevelopmentNetwork Security

Other Skills

AlgorithmsAngularJSApache SparkApplication SecurityArtificial Intelligence (AI)CC++Cloud SecurityData ScienceDockerHTMLHadoopHaskellImage SegmentationJava

About

A computer science enthusiast, who loves to accomplish complex tasks in simpler ways.

Experience

2 yrs 1 mo

New York University

Present

Google

Software Engineer

Feb 2021Present · 5 yrs 1 mo · San Francisco Bay Area

  • • Gmail

Adobe

3 roles

Research Intern

Jun 2019Aug 2019 · 2 mos

  • Implemented the very first PyTorch version of an end to end trainable Superpixel generation framework.
  • Devised a novel self supervised image segmentation algorithm based on Superpixels and Optical flow.
  • Enabled features such as Deep Product Search, Smart Crop and Region Selection in Adobe Photoshop to detect any object as compared to a limited number of supervised objects beforehand.
PyTorchImage SegmentationDeep LearningComputer Vision

Senior Member of Technical Staff (SDE - II)

Promoted

Jul 2017Aug 2018 · 1 yr 1 mo · Noida Area, India

  • Intelligent Digitization of Paper Forms: Adobe Experience Manager - Flamingo
  • Developed a web system to automatically digitize forms for clients including US government departments like medicine and finance.
  • Designed and implemented a web platform to segment and annotate form components from form images to train neural networks.
  • Lead the annotation process using the above platform by training and managing a team of 75, while assuring annotation quality.
  • Engineered heuristics for augmenting the training dataset for infrequent patterns leading to a 200% increase in the size of the training dataset as well as an 8% increase in the precision of the model.
  • Architected and trained a separate convolutional neural network for each of the form components with F1-scores above 90%.
  • Exposed Tensorflow models as an asynchronous microservice using RabbitMQ and WSGI.
  • Implemented a microservice to heuristically merge the output of the above neural networks to generate a hierarchical form structure.
Web DevelopmentNeural NetworksTensorFlowRabbitMQMachine LearningSoftware Development

Member of Technical Staff (SDE - I)

Jul 2016Jun 2017 · 11 mos · Noida Area, India

Indian institute of technology, kharagpur

2 roles

Teaching Assistant: Software Engineering

Jan 2016May 2016 · 4 mos · Kharagpur Area, India

  • Responsibilities included grading assignments and exams, conducting lab sessions and preparing supplementary reading material.

Teaching Assistant: Compilers

Jul 2015Nov 2015 · 4 mos · Kharagpur Area, India

  • Responsibilities included grading assignments and exams, conducting lab sessions and preparing supplementary reading material.

Ibm

Software Development Engineer Intern

May 2015Jul 2015 · 2 mos · India

  • Collected management logs of the cloud workload (Application/ Container) and forwarded them to the security administrator’s log server.
  • Implemented a bindable service to secure applications from OWASP Top Ten vulnerabilities using Nginx as a reverse proxy.
  • Created a one-click interface to bind the above service to any application in IBM Bluemix.

Sigmoid

Data Scientist Intern

May 2014Jul 2014 · 2 mos · Bengaluru Area, India

  • Recommender Systems:
  • Developed an end-to-end web application to explore music and movies based on popularity and ratings.
  • Developed a recommendation system on more than 100 million records with a processing time of under 2 seconds using Apache Spark.
  • Designed and created a rich web interface for the recommendation system.
  • Association Rule Mining Library(MLlib):
  • Implemented distributed Apriori Algorithm module for Association Rule Mining Library in Scala.
NginxCloud SecurityApplication SecurityNetwork SecuritySoftware Development

Education

New York University

Master of Science - MS — Computer Science

Jan 2019Jan 2020

Indian Institute of Technology, Kharagpur

Bachelor of Technology & Master of Technology in Computer Science

Jan 2011Jan 2016

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Vikas Patidar - Software Engineer | Stackforce