Avenash Kabeera, Developer in Singapore, Singapore
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Avenash Kabeera

Verified Expert  in Engineering

Software Developer

Singapore, Singapore
Toptal Member Since
December 10, 2019

Over the past decade, Avenash has worked on the entire software development lifecycle while building and managing apps from inception to client release. He’s led and supervised multiple engineering teams, but he considers himself a developer at heart. He’s experienced with back-end development (C++) and front end with React/Redux. Avenash often enjoys hacking away at a problem or testing out new ideas on the side whenever he has the time.


Spark, Python, Scala, Apache Hive, Hadoop, Object-oriented Programming (OOP)...
Scala, Python, Spark, Apache Hive, Machine Learning, Big Data, Data Pipelines...
wxWidgets, Perl, C++




Preferred Environment

Git, Visual Studio Code (VS Code), Windows

The most amazing...

...project I've worked on is building an enterprise-level portfolio-reporting batch web app that allows clients to administer report generation by the 100,000s.

Work Experience

Senior Machine Learning Engineer

2020 - 2021
  • Developed data pipelines to process massive data (100+ TB/run) from suppliers' data that is often incorrect and fragmented to map rooms with 99.9% certainty by incorporating machine learning models and various matching algorithms.
  • Worked closely with data scientists to train and integrate new machine learning models into current property mapping streamline targeting properties in the Chinese language.
  • Debugged various memory, performance, and scalability issues in Spark Jobs.
Technologies: Spark, Python, Scala, Apache Hive, Hadoop, Object-oriented Programming (OOP), Data Structures, Agile Software Development

Senior Machine Learning Engineer, Technical Lead

2020 - 2021
  • Designed and implemented new pipelines for current Spark Jobs where each task can be executed independently thus increasing the stability of production processes by over 50%, and at the same time, requiring to no dev changes to current processes.
  • Refactored Spark Job into a producer/consumer pattern which gave the ability to control how much resources each run should consume. It also allowed the execution of several instances in parallel, thus increasing the processing throughput by 25%.
  • Architected and developed a web application with a workflow for the Operations team that converted the process of adjusting the filtering algorithm in the room mapping streamline Spark Job into a self-service process, saving 2-3 development hours per week.
  • Collaborated with product owners to develop various hypotheses for displaying mapping data in the UI and implemented A/B experiments to verify hypotheses resulting in 100+ bookings increase per day.
  • Optimized core ETL job that processes around 300 million records/day, reducing memory usage by 85%.
Technologies: Scala, Python, Spark, Apache Hive, Machine Learning, Big Data, Data Pipelines, React, SQL, Technical Leadership, Engineering Management, Agile Software Development

Software Engineer

2020 - 2020
  • Designed and developed a new C++ UI and framework to replace the client's legacy process to optimize the DeltaV workflows for automation, optimizing operational efficiency and providing a better user experience.
  • Deployed software as a Windows application with Microsoft Installer to encapsulate all existing process dependencies, removing manual setup and configuration for end-users.
  • Packaged the application into a Microsoft Installer that sets up all its dependencies, allowing end-users to immediately get going.
  • Assessed various licensing models and implementation roadmaps leveraging different solution stack to develop final recommendations for the client.
Technologies: wxWidgets, Perl, C++

Lead Software Engineer

2016 - 2019
  • Initiated the project to create a unified web application, Portfolio Reporting Batcher, to replace four legacy batching apps, delivering a one-stop solution for clients' batching workflows.
  • Designed a long running infrastructure to offload Portfolio Reporting Batcher's complex operations to background processes, significantly increasing the success rate of job runs by 40%.
  • Designed a long-running infrastructure to offload portfolio reporting batcher complex operations to background processes, significantly increasing job runs' success rate by 40% (Node.js, Redis).
  • Created a centralized Batch API to orchestrate and manage 50,000+ reports per job, reducing code redundancy by over 30%.
  • Led the design and development of an automated conversion system to seamlessly migrate 10,000+ client documents and jobs onto the next-gen platform, saving product managers six months of manual work.
  • Collaborated with project managers and other engineering groups to plan and prioritize projects for engineering teams.
Technologies: Redis, AngularJS, Node.js, JavaScript, TypeScript, C++, Agile, Scrum, Engineering Management, Technical Leadership, MySQL, Perl, Object-oriented Programming (OOP), Agile Software Development

Senior Software Engineer

2011 - 2016
  • Built a prototype web application over one weekend and convinced senior management to invest in migrating the legacy Portfolio Publisher to a new web app.
  • Redesigned legacy Portfolio Batcher infrastructure from running jobs in-process to running with distributed services, improving scalability and stability without disrupting clients’ production processes.
  • Created a unified API to replace the different legacy frameworks used by three Portfolio Publisher applications, reducing the number of client issues by more than 50%.
  • Optimized the Publisher Document Manager application, shortening the runtime of loading 9000+ documents from an hour to two minutes.
Technologies: JavaScript, TypeScript, AngularJS, C++, Technical Leadership, Engineering Management, Object-oriented Programming (OOP), REST APIs, Data Structures, Agile Software Development

Software Engineer

2007 - 2011
  • Developed both the front end and back end of the portfolio publishing applications to implement major enhancements and solve client issues.
  • Built private wealth manager application from scratch, introducing FactSet into the wealth management space, now becoming the foundation of the FactSet next-generation wealth solutions.
  • Optimized portfolio lookup widgets, improving performance in speed and space by more than 50%.
Technologies: C++, Data Structures

A File Downloader Module for a Web Crawler

A Python module that can be used on its own or integrated into a web crawler for downloading media from the internet. The file downloader supports various protocols such as HTTPS, FTP, and SFTP and even has an interface where consumers can plug in their custom modules.

The file downloader is very robust in that it's able to support huge files (50GB+ range) without timing out, it's ready to automatically restart a download in the event of losing internet connection, and it allows you to control the memory usage of each download.

It is also very configurable. You can specify the number of files to download in parallel, by size, and to break each file while downloading. You can also specify the max timeout for connecting to a server as well as waiting for server activity during a file download.


C++, Python, JavaScript, JavaScript 5, Perl, TypeScript, SQL, Java, Scala


Git, Draw.io


Agile Software Development, Object-oriented Programming (OOP), RESTful Development, Unit Testing, Agile, Scrum


Windows, Visual Studio Code (VS Code), Visual Studio 2017


AngularJS, Express.js, Flask, Spark, Hadoop


wxWidgets, React, Node.js, NumPy, REST APIs


MySQL, PostgreSQL, Redis, Apache Hive, Data Pipelines


Data Warehouse Design, Quantitative Analysis, Statistics, Data Structures, Algorithms, Operating Systems, Linear Algebra, Differential Equations, Image Processing, Signal Processing, Software Engineering, Regression, Quantitative Modeling, Engineering Management, Technical Leadership, Machine Learning, Big Data

2011 - 2013

Master of Science Degree in Quantitative Methods and Modeling

Baruch College - New York City, NY, USA

2003 - 2007

Bachelor of Science Degree in Computer and Electrical Engineering

NYU Tandon School of Engineering - New York City, NY, USA


Sequence Models



Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization

Deeplearning.ai via Coursera


Structuring Machine Learning Projects

Deeplearning.ai via Coursera


Neural Networks and Deep Learning

Deeplearning.ai via Coursera


Machine Learning

Stanford University via Coursera