Vikesh Khanna

CTO

Stanford, California, United States17 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

CTO and co-founder of a Series-B AI company.
Expert in applied computer vision and deep learning.
Built core data infrastructure for Dropbox.

Stackforce AI infers this person is a SaaS expert with a strong focus on AI and data infrastructure.

Contact

khanna.vikesh@gmail.com LinkedIn

Skills

Core Skills

AiComputer VisionData InfrastructureData ProcessingMachine LearningNatural Language ProcessingGraph ProcessingCloud ComputingWeb Development

Other Skills

AJAXAlgorithmsApplied Machine LearningBackend DevelopmentBackup SolutionsCC#C++CSSComputer ScienceData ReplicationData StructuresDatabasesDebugging ToolsDjango

About

CTO & co-founder of Ambient.ai, a Series-B company backed by YC and a16z pushing the boundaries of applied computer vision. Software Engineer, designer and architect with over 10 years of experience in designing complex products across a variety of platforms. I enjoy solving challenging problems in deep learning, computer vision and large scale systems. Before founding Ambient, I worked on Dropbox's analytics data infrastructure. Previously, I have shipped products at Microsoft and LinkedIn. I am passionate about AI and the transformative influence it will have on society in the years to come. I believe we can harness the power of smart and intelligent devices to enrich our lives as well as make ourselves dramatically more productive. Looking forward to building that future.

Experience

Ambient.ai

CTO & Co-founder

Jan 2017 – Present · 9 yrs 2 mos · San Francisco Bay Area

Ambient.ai is a Series-B AI company founded by Stanford alumni and backed by YC/a16z with a mission to prevent every security incident possible. We're using state-of-the-art AI, including frontier VLMs, to solve an incredibly important real-world problem. Our investors include YC (W17), Andreessen Horowitz (a16z), Stanford StartX, SV Angel, among others.
We're hiring: https://ambient.ai/careers
If you want to be a part of a fast growing enterprise infrastructure company solving some of the most challenging and meaningful problems, reach out: careers@ambient.ai

AIComputer VisionApplied Machine Learning

Dropbox

Software Engineer

Jul 2015 – Jan 2017 · 1 yr 6 mos · San Francisco Bay Area

I was responsible for building the core infrastructure that enables Dropbox to make data-driven decisions for sales, product strategy, marketing, engineering etc. I build and support infrastructure that manages multiple petabytes of data and processes millions of messages per second.
Specifically, some of the exciting things I have been working on:
Reducing downstream job failures by making event logging type-safe (and retroactively upgrading thousands of logging channels without downtime).
Making event logging 12x faster (end-to-end) by replacing a batch-based log aggregation engine with a streaming pipeline.
Efficient (time-constrained) large scale inter-cluster data replication at a scale of over 10PB of data with millions of files.

Data InfrastructureData ProcessingEvent Logging

Stanford university

2 roles

Taught Applied Machine Learning

Promoted

Sep 2014 – Dec 2015 · 1 yr 3 mos · United States

Taught a variety of applied machine learning courses at Stanford, covering a broad range of AI topics, such as:
Natural Language Processing: Machine learning methods for extracting semantic information from unstructured text. Covered a number of applications, such as search engines, chatbots and recommendation systems.
Graph analysis: Covered the latest research on large-scale social and information networks and a number of ML techniques for their analysis.
Parallel computing: Designed coursework for "Introduction to Parallel Computing". Taught neural network optimization using openMP, MPI and CUDA.

Machine LearningNatural Language ProcessingParallel Computing

Research Assistant

Apr 2014 – Jul 2014 · 3 mos

Built Graft - A debugging tool for distributed graph processing systems (like Apache Giraph). Giraph is a distributed graph processing system built on top of Hadoop. [Paper published in ACM SIGMOD 2015: http://dl.acm.org/citation.cfm?id=2735353].
Worked with outstanding researchers in the Stanford InfoLab team to design Graft to work at scale.
Developed the backend server that collects and reads debug traces (protocol buffers) and provides a JSON-response API for the the Graft client.
Developed an interactive front-end interface that shows graph visualization, tabular summary of the graph and integrity violations.

Graph ProcessingDebugging Tools

Software Engineering Intern

Jun 2014 – Sep 2014 · 3 mos · Mountain View, CA

As part of the Profile Expressions team at LinkedIn, I worked on re-writing and building new features for the backend that powers User Recommendations and Endorsements.

Microsoft corporation

Software Development Engineer (SDE)

Jun 2011 – Aug 2013 · 2 yrs 2 mos

Windows Azure Backup - Building the first version of Windows Azure Backup for Windows 2012 server to backup file system data to Azure.
Designed and developed the deployment infrastructure of Windows Azure Backup that provides user-friendly and extensible deployment and hot-fix upgrades of WAB services.
Developed the telemetry infrastructure and pipeline that helps WAB collect usage data for continuous service improvement.

Cloud ComputingBackup Solutions

Zigndog

Co-founder

Nov 2008 – Jan 2010 · 1 yr 2 mos

Designing and developing beautiful user interfaces and websites.

Entrepreneurship development cell, iit roorkee

Tech lead

Aug 2007 – Jul 2011 · 3 yrs 11 mos

Responsible for the tech infrastructure to support EDCs online presence and media outreach. Worked with several cutting edge technologies (at the time) including a ground up re-design of EDCs website with Django.

Web DevelopmentDjango