Help & Supportcareers@gravityer.com
Principal Engineer at @nvidia Previously applied Scientist at @alexa @awslabs @aws, PhD in CS and MS in EE from Arizona State University.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
dmlc
Data Scientist
June 25, 2026 – Present
aws
Data Scientist
June 25, 2026 – Present
awslabs
Data Scientist
June 25, 2026 – Present
alexa
Data Scientist
June 25, 2026 – Present
nvidia
Data Scientist
June 25, 2026 – Present
content-localization
April 7, 2026 – Present
Localize and translate media and sync multiple speaker’s lips to translated audio.
View Projecttf-lenet
August 10, 2017 – January 25, 2021
Migrating from Theano to Tensorflow using Lenet as a case study.
View ProjectIncremental-GAN
March 6, 2017 – July 17, 2017
Just some experiments on GANs hallucinating data samples for an incremental learner.
View Projectregularizer-network
February 20, 2016 – April 27, 2016
A network that regularizes the other.
View Projectnp-mil
December 8, 2015 – October 18, 2016
Code for Ragav Venkatesan, Parag Shridhar Chandakkar, Baoxin Li "Simpler non-parametric methods provide as good or better results to multiple-instance learning." at the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.
View Projectinstagram-crawling
July 22, 2015 – November 20, 2016
Code to Crawl Down Instagram data using A BFS from some starting user and also collect MIT popularity score along with every image.
View Projectyann
July 6, 2015 – August 16, 2017
This toolbox is support material for the book on CNN (http://www.convolution.network).
View ProjectCultural Fit Analysis
The candidate's project history shows a strong focus on personal, research-oriented machine learning and data science projects. While this indicates a passion for the field, the lack of diverse project types (e.g., open-source contributions, team projects with clear business impact, or projects outside of core ML/DS) makes it difficult to fully assess cultural fit for a collaborative, product-driven environment. The listed experience roles are all 'Data Scientist' which aligns with the target role, but without details on responsibilities or team interactions, cultural fit remains largely unassessed.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The provided data primarily focuses on technical projects and work history without details on collaboration, problem-solving approaches, or communication styles.