Abhiney Kathuria

VP of Engineering

San Francisco, California, United States8 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led ML infrastructure development at Zendesk.
Built scalable AI solutions for high-impact companies.
Integrated cutting-edge ML research into practical applications.

Stackforce AI infers this person is a Machine Learning Architect with expertise in scalable AI solutions for diverse industries.

Contact

abhinaykathuria@gmail.com LinkedIn

Skills

Core Skills

Machine LearningDeep LearningComputer VisionData Analysis

Other Skills

AWS LambdaAWS SageMakerAgile EnvironmentAgile Project ManagementAmazon EC2Amazon Web Services (AWS)Apache AirflowArduinoCC++Continuous Integration and Continuous Delivery (CI/CD)Core JavaData CatalogueData EngineeringData Mining

About

I'm passionate about driving innovation in machine learning and artificial intelligence, particularly in building scalable ML infrastructure that powers real-world applications. As the Head of ML Platform at Zendesk, I lead product and engineering teams to develop an ML toolkit and foundation for advanced models, focusing on reducing the model development cycle and scaling AI solutions. In the last decade, I've had the privilege of managing and building large-scale ML and big data infrastructures at various high-impact companies such as Carsales, REA Group. My expertise spans creating robust architectures that support high throughput and low latency serving for applications in customer service, social media, online advertising, and beyond. Two things that I find exciting: 1) Bridging the gap between cutting-edge research and practical, scalable technologies that drive product development. I'm committed to integrating the latest advancements in AI and ML into scalable, reliable systems that meet the needs of end-users. 2) Understanding and enhancing the role of ML and AI engineers in business contexts. Unlike traditional software engineering, fields like ML and AI require a multidisciplinary approach, bringing together experts from various domains. My goal is to build effective teams comprising software engineers, data scientists, and domain experts, fostering a collaborative environment where innovation thrives.

Experience

Zendesk

3 roles

Senior Engineering Manager, Machine Learning

Promoted

Mar 2025 – Present · 1 yr

Engineering Manager, Machine Learning

Nov 2022 – Mar 2025 · 2 yrs 4 mos

Team LeadershipMachine Learning

Engineering Team Lead, Machine Learning Platform

Dec 2021 – Nov 2022 · 11 mos

Team LeadershipMachine Learning

Rea group

3 roles

Senior Machine Learning Engineer (Tech Lead)

Feb 2021 – Dec 2021 · 10 mos

Senior Developer - Data Platform

Promoted

Jan 2021 – Feb 2021 · 1 mo

Team LeadershipMachine Learning

Developer - Data Platform

Apr 2020 – Jan 2021 · 9 mos

Carsales.com.au

Machine Learning Engineer

Feb 2019 – Apr 2020 · 1 yr 2 mos · Melbourne, Australia

Designed and developed an ML-based fraud detection system using python for adverts and enquiries, reducing manual approval by over 30%, saving the company US$200K annually
Developed and deployed NLP model in production for detecting spam/fraud enquiries and ads, increasing customer satisfaction by over 15%
Engineered a smart cropping algorithm in python for photos to look consistent using Faster R-CNN(MXNet) Object Detection model
Used Kinesis, Elasticsearch, and Kibana to analyse and visualise WAF traffic.
Developed CI/CD pipelines for continuous training and deploying of the model in production
Collected and prepared datasets from 31 million records using pandas
Created visualisations of fraud patterns for preliminary analysis and pattern detections using matplotlib

Rmit university

2 roles

Head Tutor/Tutor

Jul 2018 – Jun 2022 · 3 yrs 11 mos · Melbourne, Australia

Sessional Tutor for Data Mining and Programming Techniques
Designed lectures and labs covering data cleaning and creating models using sklearn
Designed and supervised a special deep learning assignment using Tensorflow and Keras
Led and tutored classes of over 30 students

Research Assistant

Jul 2018 – Feb 2019 · 7 mos · Melbourne, Australia

Researched and contributed to the development of a framework (TDF) for structural modelling of agent-oriented paradigm in autonomous systems as a part of a research funding from Defence Science Technology group
Designed and developed the application using QT and mxGraph library for modelling of dynamic decision making
Partnered with Melbourne Renegades cricket team to help coaches analyse player's performance with the help of Machine Learning
Built a Computer Vision Algorithm for automatic clipping of videos and tagging it, helping coaches highlight key problems to each player
Used Hexoskin to view each player's metrics and analyse it after each training session. Led a team of 5 students to develop a dashboard and create predictions about fatigue
Setup CI/CD pipelines for building the versions on Linux and Windows
Created examples for agent-based online auction system using TDF for researchers in the Defence Group to use

Tata consultancy services

Java Software Engineer

Jul 2016 – Jul 2017 · 1 yr

Developed and unit tested interfaces using Java for MDM and SWIFT Messages using SWIFT Protocol.
Developed user-interactive dynamic web pages for Clearing and Deposit Systems using JavaScript.
Developed and executed functional, syntactical and service integration test cases.
Implemented and executed test cases for multiple depositories and clearing solutions
Liaised with clients to create requirement documents for their proposals
Received a perfect 5/5 performance rating in TCS’s Initial Learning Program (ILP); conferred “ILP Kudos” award as an appreciation for excellent performance
Selected amongst 150 employees for a special outbound learning program with a group of Japanese associates; participated in team building activities & analyzed case studies for requirement gathering