Rajat Singhal

Software Engineer

India6 yrs 7 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Developed features for AirSim and ArduPilot integration.
National winner of Microsoft CodeFunDo++ 2019.
Experience in low-latency, high-performance applications.

Stackforce AI infers this person is a Robotics and Software Engineering professional with experience in Aerospace and Media industries.

Contact

Skills

Core Skills

Software DevelopmentEmbedded SystemsRobotics

Other Skills

3D Obstacle AvoidanceAIAirSimAlgorithmsAmazon Web Services (AWS)AmplitudeApache KafkaApache SparkBSD SocketsBashCC++CMakeCUDAComputer Science

About

Currently working in the Core Engineering team at Tower Research Capital, I'm interested in learning to build and design low-latency, high-performance applications and in areas such as Distributed Systems, Machine Learning, Robotics and Systems Engineering. I've completed my B. Tech from the Computer Science department in IIT Madras in 2021. Started my open-source journey in GSoC 2019 with ArduPilot.org, a versatile open autopilot software for drones and other autonomous systems. Currently, I work more on AirSim, having developed several new features, bug fixes, unit-testing, CI/CD & improved documentation. I’ve also worked as a Software Development Intern at Disney+ Hotstar in April-June 2020. I’ve been a part of interdisciplinary projects and teams like UAVs for Disaster Management & Avishkar Hyperloop. We were the National Winners of Microsoft CodeFunDo++ 2019 for our work on autonomous swarm drones for surveillance in disasters. And Avishkar Hyperloop being the only Asian team in the Top 21 finalists of the SpaceX Hyperloop Pod Competition. Apart from this, I’ve taken various courses related to Systems Engineering and core CS and use other online methods to explore my interests. Reading books is one of my major hobbies, and I enjoy reading technical books and fiction novels and keeping myself up to date with the latest news and technologies through blog posts and articles.

Experience

6 yrs 7 mos

Total Experience

1 yr 6 mos

Average Tenure

5 yrs

Current Experience

Tower research capital

4 roles

Low Latency Software Developer

Jul 2025 – Present · 11 mos

Working on the low latency market data & trading stack as part of LimeStone trading team

Software Engineer III

Jan 2025 – Aug 2025 · 7 mos

Order Entry Core, Trading Platform

Software Engineer II

Promoted

Feb 2023 – Jan 2025 · 1 yr 11 mos

Order Entry Core, Trading Platforms

Software Engineer I

Jun 2021 – Feb 2023 · 1 yr 8 mos

Order Entry Core, Trading Platforms

Hotstar

Software Engineering Intern

Apr 2020 – Jun 2020 · 2 mos

● Enhanced the monitoring & alerting of events, by integrating Amplitude & Prometheus platforms
● Wrote Python services which improved the alerting granularity from hourly to 5 min & increased limitations of 10 metrics to 300 metrics, with an error rate of ~5%
● Designed a generic streaming pipeline to process raw events using Apache Spark & Kafka
● Defined a simple interface for Playable Ads & implemented it on a demo Android app + advertisement

PythonApache SparkApache KafkaSoftware Development

Ardupilot

Student Developer - Google Summer of Code

May 2019 – Sep 2019 · 4 mos

ArduPilot is the most advanced, full-featured and reliable open source autopilot software available, capable of controlling any vehicle system imaginable, from conventional airplanes, multirotors, and helicopters, to rovers and boats and even submarines.
During the course of the project, support for AirSim simulator was added for ArduPilot firmware. The Firmware-Simulator interface utilized BSD Sockets for communication alongwith several other novel features.
For details, see - https://summerofcode.withgoogle.com/archive/2019/projects/4737458481135616/

Uavs for disaster management

Robotics & CV

Apr 2018 – Sep 2019 · 1 yr 5 mos

Swarm of Autonomous Drones equipped with Computer Vision & AI for locating people and surveillance in disasters
● Tested 3D Obstacle Avoidance Algorithms using Stereo & Depth Cameras in simulations as well as on hardware
● Integrated Obstacle Avoidance with Path-Planning algorithms for multiple agents to achieve autonomous surveillance of a large region
● Generated training data for Deep Learning & tested drone POV person detection in simulations and hardware
● Achieved live-video transmission over WiFi & GSM network using FFmpeg and Azure Media Services