NVIDIA

I work with  Bay Area Automotive accounts (OEMs, Tier-1's & Startups), Hyper-scale Cloud Service Providers,  System Integrators and  Service Delivery Partners on GPU based end-to-end Autonomous driving solutions (Training, Simulation and Validation ).

https://www.nvidia.com/en-us/data-center/dgx-a100/
https://www.nvidia.com/en-us/self-driving-cars/simulation/

Sr. Solutions Architect - North America Enterprise Automotive Accounts 

The NVIDIA DRIVE Constellation™ AV simulator delivers a scalable, comprehensive, and diverse testing environment for Autonomous Driving Companies.
Read More about it at : https://www.nvidia.com/en-us/self-driving-cars/drive-constellation/

Solutions Architect - Autonomous Vehicle Simulation / Data Scientist 3

Engaged with highly seasoned Data Science teams at Telecommunication F500s in migration of traditional Machine Learning based Network Anomaly Detection approaches to scalable GPU based Deep Learning methods.

Collaborated with AWS in prototyping GPU-accelerated ML workflows powered by NVIDIA RAPIDS on  Sagemaker through convincing benchmarks, value-propositions and user-stories.

Jointly developed a GPU accelerated Domain-specific Automatic Speech-to-Text (STT) solution built on NVIDIA's OpenSeq2Seq framework for training acoustic and language models.

Architected an end-to-end DL solution on Kubeflow utilizing NVIDIA's SW stack such as DALI, TF-AMP, TensorRT and the TRITON inference server. Showcased the demo at global conferences of leading CSPs.

Redirected clear and actionable feedback to product and engineering teams based on customer critique and identified areas of greatest opportunity.

Lead regular technical discussions, product presentations and solutions  to everyone from developers to Global Heads.

Data Scientist 2

AI Strategy

Worked on a National Institute of Health funded project for developing the Deep Learning backend of a low-cost Breast cancer detection device targeted at low-income economies.

Applied image processing and CV libraries (OpenCV, OpenGL, PIL, etc.) to manipulate training data, automate labeling and update classification algorithms

Implemented and fine-tuned InceptionV4 based transfer learning models on Tensorflow.

Created a Web Application using Bootstrap and Flask for clinicians to interact with the tensor-flow model and obtain the output of the diagnosis.

Coordinated with teams in Mexico to establish a DICOM Server for transferring images from the  Ultrasound Device to the database over an internal network.

Software Engineering Intern

Rutgers University

Conducted code along sessions in class and assisted teams with product prototyping for the course Applied AI Concept to Market(16:137:602).

Teaching Assistant

Nokia Bell Labs

Developed Market models, Sales forecasts and Adoption curves for Connected Cars and Industrial
Internet of things to understand their impact on the revenue opportunities, cost containment and
network efficiency of telecom operators.

Formulated Business Models and Monetization Opportunities for Telecom Operators by analyzing
relevant use cases.

Assisted in performing telecom customer churn analysis and proposed short-term and long-term business and operational strategies.

Business Modelling Intern 

Mercedes-Benz Research and Development India

Worked on the simulation and control of the Electric-Drive in the Trucks and Buses vertical.

Supported the design and development of simulation tools for testing vehicle performance
    parameters on MATLAB.

Vehicle Test data Analysis using Python

R&D Engineering Intern

I blend my engineering and quantitative background with strong storytelling skills to accelerate Autonomous Driving workloads on NVIDIA's GPU computing platform. A  customer's success is my success.

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