Last updated: 26th July 2022

Dheeraj Rajaram Reddy  Bangalore, India

Work Experience

Member of Technical Staff July 2020 - Present
  • Part of the SpotIQ team building algorithms for AI-driven automatic insights.
Engineering Intern January 2020 - June 2020
  • Designed and implemented a containerized execution engine for safely running user scripts.
  • Worked on query-aware data-generation for testing ThoughtSpot’s database engine.
  • Worked on improving the CI and build systems for Java services.
Open Source Maintainer and Core Contributor June 2019 - May 2020
  • Implemented several core layers, optimizers, models, and the first TF2.0 native implementation of CRFs.
  • Maintained the CI and package release pipelines.
Intern May 2019 - June 2019
  • Rewrote a Spark data-processing pipeline to make it 3x faster and less prone to Java OOM errors.
  • Added deep learning support for their automated ML platform using TensorFlow.
  • Built a distributed KNN algorithm using Hybrid Spill-trees.
Team Leader and Planning Head February 2017 - February 2019
  • Lead a team of 60 engineering students, handling both the technical and managerial aspects of a robotics team.
  • The team placed 1st worldwide at Intelligent Ground Vehicle Competition (IGVC) 2019.
  • Won the Mahindra Rise Prize Challenge for building the best driveless car for Indian roads.
  • Designed, implemented and tested the software stacks of autonomous bots and cars.
Research Assistant January 2018 - December 2019

Manipal Institute of Technology

  • Publication: B. J. Bhatkalkar, D. R. Reddy, S. Prabhu and S. V. Bhandary, “Improving the Performance of Convolutional Neural Network for the Segmentation of Optic Disc in Fundus Images Using Attention Gates and Conditional Random Fields,” in IEEE Access, vol. 8, pp. 29299-29310, 2020


Manipal Institute of Technology 2016 - 2020

B. Tech Computer Science and Engineering

  • Minor in computational mathematics
  • CGPA: 8.25/10

Selected Projects & Contributions

  • Open source: Contributions to various OSS projects, including TensorFlow, PyTorch Glow compiler, etc.
  • Shadesmar: A high-performance C++ IPC library that uses shared memory for communication. Supports RPC and pub-sub.
  • SummaryDB: A database written in Go for storing colossal amounts of time-series data. Uses window-based aggregations for compressing data.
  • Technical blog: Authored several technical articles on programming, designs, concepts, challenging problems I’ve faced, and computers in general.
  • ReiLs: A reinforcement learning framework for faster modular prototyping, deployment and benchmarking of Deep-RL algorithms. Built using TensorFlow, MPI and NCCL.


  • Languages: C, C++, Java, Go, Groovy, Haxe, Python, Rust
  • Build Systems: Bazel, CMake, Gradle
  • CI/CD: GitHub Actions, Jenkins
  • Deep Learning: CuDNN, Jax, PyTorch, TensorFlow
  • Parallel Programming: Arm Neon, CUDA, Intel SIMD, Halide
  • Distributed Computing: Docker + Kubernetes, MPI
  • RPC/serialization: Cap’n Proto, Messagepack, Protobuf + gRPC, Thrift
  • Miscellaneous: OpenCV, ROS, Spark

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