Abhinav Deep Singh

Senior Software Engineer

Bengaluru, Karnataka, India8 yrs 4 mos experience
Most Likely To SwitchHighly Stable

Key Highlights

  • Expert in Machine Learning and AI technologies.
  • Developed autonomous vehicle technology with successful permits.
  • Achieved high performance in deep learning projects.
Stackforce AI infers this person is a Machine Learning Engineer with expertise in AI-driven solutions for autonomous systems.

Contact

Skills

Core Skills

Artificial Intelligence (ai)Machine LearningData Science

Other Skills

TensorFlowDeep LearningCaffeComputer ScienceMathematicsPython (Programming Language)C++PyTorch

About

Currently working in Google Search Discover as a Software Engineer.

Experience

8 yrs 4 mos
Total Experience
2 yrs 1 mo
Average Tenure
5 yrs 10 mos
Current Experience

Google

2 roles

Senior Software Engineer

May 2024Present · 1 yr 11 mos

Senior Software Engineer

Jun 2020May 2024 · 3 yrs 11 mos

Artificial Intelligence (AI)Machine Learning

The university of texas at austin

Graduate Research Assistant

Jan 2020May 2020 · 4 mos · Austin, Texas Metropolitan Area

  • Worked with Prof. Raymond Mooney on Causal Graphs for Language Understanding.

Google

Software Engineer Intern

May 2019Aug 2019 · 3 mos · Sunnyvale, California, USA

  • Worked on Time-Series Forecasting and Anomaly Detection.
  • Analysed different available datasets to check seasonality and holiday effects.
  • Worked on Data and ML Pipeline, to continuously ingest, and train neural network
  • models, on new data, using Tensorflow Extended library.

Samsung electronics

2 roles

Software Engineer

Sep 2016Aug 2018 · 1 yr 11 mos · Seoul Incheon Metropolitan Area

  • Worked on developing Samsung’s Autonomous Vehicle.
  • Worked on handling dynamic object detection, like pedestrians and cars
  • using cameras and LiDARs using deep CNNs implemented in Tensorflow.
  • Successfully got Highway Autonomous Driver Permit for the car in August 2017 after test conducted by Korean Transportation Authority. The car then successfully navigated around in the city in loop of 10 km.

Software Engineer Intern

May 2015Jul 2015 · 2 mos · Gyeonggi, South Korea

  • Helped a robot decide navigable indoor space in real time by training a deep neural network using Caffe with various images of household objects and obstacles (like door thresholds, table bottoms, etc.).
  • Achieved the F1-score of 90.4% on the dataset curated by the company.

Education

The University of Texas at Austin

Master of Science - MS — Computer Science

Jan 2018Jan 2020

Indian Institute of Technology, Delhi

Bachelor of Technology - BTech — Computer Science and Engineering

Jan 2012Jan 2016

INSA Lyon - Institut National des Sciences Appliquées de Lyon

Exchange Student — Computer Science

Jan 2014Jan 2014

Indian Institute of Technology, Delhi

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