Sunil Patel
Data AnalystAI 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
Manager Solutions Architecture and Engineering @ Nvidia | ML/DL | Generative AI | Model Optimisation
With 13 years of deep experience in Deep Learning, I have witnessed firsthand the remarkable transformation of NVIDIA from a company valued at a few hundred billion to a multi trillion-dollar powerhouse, driving the AI revolution. My journey began with Conversational AI, where I contributed to developing and deploying advanced language models for a variety of applications. At NVIDIA, I have been deeply involved in optimizing and scaling Deep Learning models, focusing on large-scale training and inference workloads. My work includes model optimization, profiling, writing optimized operations, and ensuring scalable deployments over GPUs. I’ve also gained hands-on experience with LLM fine-tuning and RAG workflows, enabling AI datacenters to handle massive LLM training runs. Now, I am dedicated to helping customers realize AI-driven datacenters capable of running these cutting-edge models at scale, pushing the boundaries of what’s possible in AI.
Indian Institute Of Information Technology Allahabad
Master of Technology - MTech, Information Technology
January 1, 2013 – January 1, 2015
NVIDIA
Conglomerates & Industries | Manager Solutions Architecture and Engineering
March 1, 2025 – Present
NVIDIA
Data Scientist - IV Deep Learning
June 1, 2021 – Present
NVIDIA
Data Scientist - III Deep Learning
November 1, 2019 – June 1, 2021
NVIDIA
Solutions Architect - Deep Learning
July 1, 2019 – November 1, 2019
Innoplexus
Data Scientist - Deep Learning
November 1, 2017 – June 1, 2019
Eschborn, Germany
GVK
Senior Research Associate - Deep Learning
May 1, 2016 – November 1, 2017
Hyderabad Area, India
Tata Group
Software Engineer (Artificial Intelligence R&D)
August 1, 2015 – May 1, 2016
Supercomputing Facility
Internship
May 1, 2014 – July 1, 2014
IIT-Delhi
Developing a Custom Language Translation Engine for Life Science
April 1, 2018 – July 1, 2018
Developing Language translation engine which understands the nuance of biomedical language. Tools/Technology : OpenAI Transformer, Nvidia-Docker, GPU
Primary/Secondary Clinical Trial Linking
January 1, 2018 – April 1, 2018
Linking clinical trial as primary or secondary by comparing the content of clinical trial with millions of research papers. Tools/Technology: Skip-thought Sentence vectors, Siamese Networks, Pytorch, GPU Provisional patent in the United States: US16145828
Document Comparison
November 1, 2017 – January 1, 2018
Detecting syntactic and semantic similarity between two documents also detect Insertion, deletion, and Modifications. Tools/Technology: Skip-thought Sentence vectors, Siamese Networks, Pytorch, GPU Provisional patent in the United States: US16143976
Market Hawk
May 1, 2017 – August 1, 2017
To constantly see what's trending in news, A generalized end to end solution utilizing Google news, Twitter handles, LinkedIn pulse and many more sources. Solutions that can assimilate gigs of data and present you with the nice dashboard of relevant plots. # GPU #Keras #django
Data Extraction Form Strips Of Medicines
January 1, 2017 – April 1, 2017
Extracting information such as Mfg date, Exp date, batch number and active ingredient from medicinal strips using YOLO and other image processing techniques. Tools/ Technology used:- Tesseract, Pytorch ,Python
Developed Highly Scaleble Named Entity Resolution utilizing GPU Computing
May 1, 2016 – December 1, 2017
Completed and delivered a general purpose framework for any kind of Named Entity Resolution (NER) problem. The solution uses state of art ensemble model of Convolutional Network and Long Short-Term Memory (LSTM), runs on GPU to deliver the best in comparison to conventional NER solutions. #nvidia-GPU #tensorflow #NER
Financial Reconciliation using Deep Learning
August 1, 2015 – April 1, 2016
AI-driven reconciliation for banking financial record linkage. Developed Deep Learning-based, Scalable architecture on Spark to process a high volume of banking data. Tools/Technology used: H2O. Python, Spark
Conversational Interface
August 1, 2015 – November 1, 2015
For internal IT service enhancement and as a part of Ignio (TCS's IT Cognitive System for enterprise IT Ops) Completed a project on building conversational system using Natural Language Processing utilizing Word2Vec and DNN. Tools/ Technology used: - H2o, Gensim, Python
DeepInteract: Deep Neural Network Based Protein-Protein Interactions Prediction Tool
January 1, 2015 – March 1, 2015
A Deep belief network performed Amazingly well in prediction 3D protein-protein interaction. This project was part of my master's thesis to outreach my research work. Deep belief networks to predict protein-protein interaction at scale.
Machine Learning by Stanford University
Coursera Course Certificates
June 24, 2026 – Present
IBM Certified Application Developer - Cloud Platform V1
IBM
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Wireless Communications for Everybody
Coursera
June 24, 2026 – Present
Deep Reinforcement Learning Nanodegree
Udacity
June 24, 2026 – Present
Computer Vision for Industrial Inspection
NVIDIA
June 24, 2026 – Present
Neo4j Certified Professional
Neo4j
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Building Conversational AI Applications
NVIDIA
June 24, 2026 – Present
Cognitive technologies for business
NovoEd
June 24, 2026 – Present
Introduction to Natural Language Processing
Coursera Course Certificates
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Fundamentals of Deep Learning for Multi-GPUs
NVIDIA
June 24, 2026 – Present
Fundamentals of Deep Learning
NVIDIA
June 24, 2026 – Present
Applications of AI for Predictive Maintenance
NVIDIA
June 24, 2026 – Present
C++ for Game Development
Udemy
June 24, 2026 – Present
Building Transformer-Based Natural Language Processing Applications
NVIDIA
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience across various domains (finance, healthcare, IT, autonomous driving, life sciences) and a strong focus on cutting-edge AI technologies (Deep Learning, LLMs, GPU acceleration) suggest a proactive and innovative mindset. The progression through NVIDIA roles indicates an ability to thrive in a high-performance, technology-driven environment. The breadth of projects and certifications aligns with a culture that values continuous learning and diverse technical contributions. However, the target role is 'Data Analyst', which might be a mismatch for the candidate's deep specialization in Deep Learning and MLOps. While the skills are transferable, the core focus of a Data Analyst role might not fully leverage the candidate's advanced AI/ML engineering expertise.
Soft Skills & Operational Fit
The candidate's project descriptions and career progression suggest a strong problem-solving orientation and a drive for technical excellence. The numerous certifications indicate a commitment to continuous learning. While direct soft skill assessments are not available, the leadership roles at NVIDIA imply strong communication and collaboration skills necessary for managing solutions architecture and engineering.