Varun Nasery
Computer VisionAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Engineering @ Meta
Engineering Leader and ML Systems Architect with 12+ years of experience bridging advanced AI research and production reality. Currently leading cloud offload systems for Meta Reality Labs, powering low-latency ML inference and photorealistic rendering for Codec Avatars and 3D environments. I operate as a highly technical leader, focusing on the intersection of computer vision, distributed systems, and edge-to-cloud AI. Key Technical Impacts: * Optimization & Infrastructure: Improved Codec Avatar throughput 10x (TensorRT) and reduced transmission latency 5x for cloud-offloaded scene understanding. * Edge & Wearable AI: Shipped on-device computer vision models for Ray-Ban Meta smart glasses. CV Foundations: Built scalable systems for 3D bounding-box generation, visual search, and catalog de-duplication. I thrive on working through ambiguous, cross-functional challenges to turn multimodal AI breakthroughs into reliable, consumer-facing products.
University of Southern California
Master of Science, Electrical Engineering (Multimedia and Creative Technologies )
January 1, 2011 – January 1, 2013
Visvesvaraya National Institute of Technology
Bachelor of Technology, Electronics and Communication Engineering
January 1, 2007 – January 1, 2011
Meta
Engineering Manager
January 1, 2019 – Present
San Francisco Bay Area
Myntra
Machine Learning Engineer
June 1, 2017 – January 1, 2019
Palo Alto, CA
DAQRI
Computer Vision Engineer
April 1, 2016 – June 1, 2017
Sunnyvale, CA
Intel Corporation
Computer VIsion Software Engineer
August 1, 2013 – April 1, 2016
Santa Clara, CA
Intel Corporation
Software Engineering Intern
January 1, 2013 – May 1, 2013
Santa Clara
TiVo
Engineering Intern
May 1, 2012 – August 1, 2012
GlobalLogic
Summer Project Trainee
May 1, 2010 – May 1, 2011
AudioSense: A hand gesture controlled audio player
January 1, 2012 – May 1, 2012
• Developed a hand gesture recognition based music playback system on a Texas Instruments DaVinci 6437 DSP using a Kinect depth camera for input • Features implemented : play, pause, shuffle, mute, skip songs audio equalization
Video Summarization
September 1, 2011 – December 1, 2011
• Implemented an algorithm to extract the important scenes from a video to produce a comprehensive synopsis • Performed analysis of video shots on the basis of the color, motion and audio levels of the shots and then a metric was developed to choose the most important shots in the video
Indoor positioning using video surveillance infrastructure
August 1, 2010 – April 1, 2011
• Designed a barcode based system using OpenCV for localization of people/objects in an indoor environment • The barcodes are read by cameras and 3D pose estimation of the barcode is performed for localizing the object
Cultural Fit Analysis
The candidate's experience spans large corporations (Meta, Intel), e-commerce (Myntra), and AR/VR startups (DAQRI), indicating adaptability to various organizational cultures. The project diversity, from academic research to product development, suggests a broad interest and ability to contribute to different types of initiatives. The progression to a management role at Meta also implies a capacity for leadership and mentorship, which can be a strong cultural asset. The target role of 'Computer Vision' aligns perfectly with the candidate's professional history and project work.
Soft Skills & Operational Fit
The candidate's career progression to Engineering Manager at Meta suggests strong leadership, project management, and team collaboration skills. The diverse project experience indicates adaptability and problem-solving capabilities. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.