Sudeep R.

Software Engineer

Bengaluru, Karnataka, India6 yrs 9 mos experience

Key Highlights

Expert in Kernel and Backend Development.
Proficient in Deep Learning and NLP technologies.
Experience in developing scalable distributed systems.

Stackforce AI infers this person is a Backend-heavy Software Engineer with expertise in AI and distributed systems.

Contact

Skills

Other Skills

C++CMicrosoft OfficePythonTensorFlowVerilogAndroid DevelopmentJavaLinuxKubernetesAlgorithmsData Structures

About

Experienced in Kernel Development, Backend Development, Deep Learning, and Natural Language Processing.

Experience

6 yrs 9 mos

Total Experience

2 yrs 8 mos

Average Tenure

1 yr 5 mos

Current Experience

Google deepmind

Software Engineer

Nov 2024 – Present · 1 yr 5 mos · Bangalore Urban, Karnataka, India · On-site

Google

Software Engineer

May 2022 – Nov 2024 · 2 yrs 6 mos · Bengaluru, Karnataka, India

Google Cloud Security

Appdynamics

2 roles

Software Engineer III

Promoted

Oct 2021 – May 2022 · 7 mos

Designing and Developing Scalable Large scale Distributed Systems for Synthetic User Monitoring

Software Engineer

Jul 2019 – Oct 2021 · 2 yrs 3 mos

Rise lab, indian institute of technology madras

SHAKTI Processor Project

Aug 2018 – Apr 2019 · 8 mos · Tamil Nadu, India

Was part of the team building one of a kind open-source RISC-V based Linux chip called the Shakti Processor.
Was responsible for writing a Linux device driver to allow the processor to interface with external memory using Quad-SPI.

Chair of operating systems, technical university of munich

2 roles

ArgOS Operating system

May 2018 – Jul 2018 · 2 mos · Garching, Bavaria, Germany

Updated the Genode framework used in the ArgOS operating system which is being built to handle the increasing number of software-based tasks in self-driving and software heavy automobiles.
Facilitated the use of the more secure and reliable seL4 microkernel which is supported by the latest iteration of Genode instead of the Fiasco.OC L4 microkernel.

MALSAMi- RNN based Schedulability Analysis for Migration of Software Components at runtime

May 2018 – Jul 2018 · 2 mos · Garching, Bavaria, Germany

Implemented and trained a Recurrent Neural Network to schedule tasks between processors at runtime.
Optimized to find the most efficient and accurate way for running software components in a common runtime environment.

Rise lab, indian institute of technology madras

2 roles

Genode Microkernel

Nov 2017 – Apr 2018 · 5 mos · Greater Chennai Area

Working under Prof. Dr. V. Kamakoti at IIT Madras to develop new software Drivers for different peripherals to work with the Genode microkernel.
The Genode OS Framework is a tool kit for building highly secure special-purpose operating systems.

Large Scale Multilingual Transliteration

May 2017 – Jul 2017 · 2 mos · Greater Chennai Area

Working under Prof. Dr. Mitesh Khapra at IIT Madras to develop a model that can transliterate words between different languages with high accuracy.
The model was implemented using TensorFlow and consists of a deep GRU network with encoder and decoder layers that takes the embedding of a word in one language and gives its transliteration in the script of the required language. In order to train the model, we created our own dataset by scraping over 2 million proper nouns from Wikidata in 40 different languages.