Krish Ravindranath
ML EngineerMachine Learning Engineer
Pindrop
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Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
👋 hello
Georgia Institute of Technology
Bachelor of Science (BS), Computer Engineering
January 1, 2013 – January 1, 2016
Intelligent Instruments Lab
Visiting Researcher
July 1, 2022 – July 1, 2022
Reykjavík, Capital Region, Iceland
Pindrop
Senior Machine Learning Research Engineer
April 1, 2021 – Present
Brooklyn, New York, United States
Flock Safety
Machine Learning Engineer
February 1, 2019 – April 1, 2021
Atlanta Metropolitan Area
Autonomous Fusion
Software / AI Engineer
January 1, 2017 – January 1, 2019
Atlanta Metropolitan Area
Georgia Tech Center for Music Technology
Research Technician
June 1, 2016 – August 1, 2016
Wheego Technologies
Summer Engineering Intern, Fall Engineering Intern
June 1, 2016 – December 1, 2016
Atlanta Metropolitan Area
Microland Limited
Procurement Intern
June 1, 2015 – August 1, 2015
Bengaluru, Karnataka, India
Georgia Tech Center for Music Technology
Under the Couch - Master of Ceremonies
January 1, 2015 – May 1, 2016
Georgia Tech VIP Program - Robotic Musicianship
Undergraduate Researcher
August 1, 2014 – December 1, 2016
Atlanta Metropolitan Area
Georgia Tech VIP Program - Secure Hardware
Undergraduate Researcher
January 1, 2014 – May 1, 2014
Atlanta Metropolitan Area
Bonzai Media Works
Research Intern
July 1, 2012 – August 1, 2012
Pune, India
Moog bed
February 1, 2021 – February 1, 2021
Awarded second place for building the moog bed
Noise Blender
April 1, 2020 – April 1, 2020
Awarded an honorable mention - best performance - for making a smoothie with a synthesizer
Car Auditory Response System
February 1, 2019 – February 1, 2019
Awarded second place for building a synthesizer into a car
Synth Kalimba
February 1, 2018 – February 1, 2018
An analog electric instrument built around the Moog Werkstatt synthesizer, inspired by the Mbira (or Kalimba). Metal tines on the front are tapped or plucked to play different notes. The plucks of the tines are picked up by piezo pickups on the two wooden bridges and used to modulate the sound. Two soft pressure pads on the back of the instrument allow further modulation by varying the amplitude and the low frequency oscillator rate.
Sigmoido
February 1, 2017 – February 1, 2017
Sigmoido is a stringed controller for the Moog Wekstatt synthesizer. It has six strings- three on each side, with five frets on each string. One side controls pitch in semitones, much like the bottom three strings of a guitar. The strings on the other side are more unique- one enables jumping pitch in fifth and octave intervals, the other controls the low frequency oscillator (LFO) rate, and the final string controls the filter. The LFO and filter are continuous parameters that are traditionally controlled using a continuous input such as a dial. Controlling them using discrete frets allows for a different interaction experience with the sound. Two central knobs control the envelope (attack and decay) of the sound. The string and fret being played are detected by measuring different resistance combinations, and all of the processing is done on an Arduino Uno.
Audio Reconstruction
August 1, 2016 – April 1, 2017
Worked in a small team to train a deep autoencoder network with TensorFlow, with the goal of recreating a piece of music using other music.
Detection and Analysis of Binaural Beats in EEG Signals
March 1, 2016 – April 1, 2016
My team setup an experiment to analyse the effects of binaural beats using EEG signals. A binaural beat is an imaginary tone created in the brain when tones of two different frequencies are simultaneously presented to each ear. Certain binaural beats have been claimed to have therapeutic or stimulating effects. We sought to find these imaginary tones in the EEG signals through brainwave entrainment, and to measure any differences in brainwaves of different frequencies when listening to different binaural beats, using pink noise as a control.
Drone Pedalboard / Analog Shruti Box
February 1, 2016 – February 1, 2016
Participated in the 2016 Guthman Student Design Challenge. My team built a pedal board with the Moog Werkstatt synthesizer on it. The Werkstatt features a single voltage controlled oscillator, so we hacked it to allow the use of the low frequency oscillator as a second voltage controlled oscillator. These two oscillators were programmed via an Arduino to play a base note upon resetting the Arduino, and buttons placed at the base of the pedal board were used to change the pitch of each oscillator. The buttons were programmed to allow the user to move up or down the Mixolydian scale on each oscillator. We also connected a force sensitive resistor to the Arduino, allowing the user to use a foot tap to accent the drones. The device allows the user to play a handheld instrument at the same time, allowing it to serve as an interesting accompaniment.
Guitar Tablature Peripheral with Real Time Recording
January 1, 2016 – December 1, 2016
The Guitar Tablature Program is an integrated hardware and software system to track and record guitar tablature as a guitar is played in real time. The project was created to allow amateur guitar players to record jam sessions without having to pause to write down melodies and progressions. The system comprises of a noninvasive external pickup, easily mountable to the body of the guitar, some hardware circuitry, an embedded system, and a computer program. The external hexaphonic pickup passes the raw analog signal from each string to the hardware circuitry, which filters out harmonics, sustains the signals, and passes them to an embedded system, an ARM microcontroller. The microcontroller determines which strings are being played and what notes are being played on them, and sends this information to the front-end computer program via USB. The program parses this information as tablature and displays it in real time using an intuitive and user friendly interface. Once a recording has ended, the user is able to edit the recording and save it for future use. I worked mainly on the software/ embedded side of the project.
Wearable Device for the Detection of Hypothermia Using Photoplesmography
December 1, 2015 – Present
Created a glove with a built in vibration motor and PPG sensor to detect blood oxygen saturation levels and trigger vibrations to alert the user of dangerously low blood oxygenation.
Drone Machine
February 1, 2015 – February 1, 2015
Participated in the 2015 Guthman Student Design Challenge- a hackathon run by the Georgia Tech Center for Music Technology in collaboration with Moog Music. My team built an instrument that mapped certain parameters on a synthesizer to the velocity of rotating disks, and the frequency and amplitude to a touch-sensitive strip potentiometer. We also added two drum pads to provide percussion.
TwerkBox
October 1, 2013 – October 1, 2013
Participated in the Fall 2013 HackPrinceton hackathon. My team created a charging station that backed up important data stored on a phone to a Raspberry Pi while the phone charged.
Machine Learning Data Lifecycle in Production
Coursera
June 24, 2026 – Present
Introduction to Machine Learning in Production
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse personal projects, particularly in music technology and bio-signal analysis, demonstrate a strong curiosity and interdisciplinary approach. Their professional experience spans startups (Flock Safety, Autonomous Fusion) and research labs (Intelligent Instruments Lab, Georgia Tech Center for Music Technology), suggesting adaptability to different organizational cultures. The focus on ethical AI at Flock Safety aligns with a responsible and thoughtful approach to technology development. The breadth of their projects and roles indicates a candidate who is likely to be a proactive contributor and a good fit for an innovative, research-oriented culture.
Soft Skills & Operational Fit
The candidate's experience in forming and running an internal ethics committee at Flock Safety suggests strong ethical awareness and leadership potential. Their involvement in various hackathons and personal projects indicates a proactive, innovative, and hands-on approach to problem-solving. The descriptions of their work imply an ability to operate effectively in dynamic environments, contributing across multiple facets of a project.