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Machine Learning Engineer with 4 years of experience building production AI systems across speech, vision, and NLP. Currently at Ringg.ai, leading ML infrastructure for real-time conversational voice AI — covering model training, optimization, inference serving, and deployment at scale. Previously: → Shiprocket: Built NL2SQL systems, speech engines for call analytics, Graph ML for product classification → FieldGenie: Led team of 5, delivered ML solutions for oil & gas (predictive maintenance, RAG systems, MLOps pipelines) → Artivatic: Face liveness, document OCR, medical image classification for insurance underwriting → Spyne: Computer vision pipelines, YOLO detection, model compression for edge deployment Domains: Speech AI • Computer Vision • NLP • MLOps • LLMs/RAG B.Tech ECE, GGSIPU | Kaggle 2x Expert | Kaggle Days Delhi Co-organizer (50+ meetups)
Guru Gobind Singh Indraprastha University
Bachelor of Technology - BTech, Electronics and Communications Engineering
January 1, 2018 – January 1, 2022
Navy Children School
All india senior secondary examination, Phy,chem, maths
January 1, 2003 – January 1, 2018
Ringg AI
Founding ML Engineer
September 1, 2025 – April 1, 2026
Bengaluru · Hybrid
Shiprocket
Machine Learning Engineer
October 1, 2024 – September 1, 2025
Gurugram, Haryana, India · On-site
SLB
Lead Data Science Consultant
July 1, 2024 – October 1, 2024
Gurugram, Haryana, India
IOT++
Machine Learning Architect
June 1, 2024 – October 1, 2024
Houston, TX · Remote
Career Break
Professional development
January 1, 2024 – June 1, 2024
Artivatic.ai
Data Scientist
June 1, 2023 – December 1, 2023
Gurugram · Hybrid
Spyne
Research Engineer I
April 1, 2023 – June 1, 2023
On-site
Spyne
Computer Vision Engineer
May 1, 2022 – March 1, 2023
On-site
SuperZop
Computer Vision Engineer
March 1, 2022 – May 1, 2022
Remote
Scanta
Machine Learning Engineer
August 1, 2021 – October 1, 2021
Robofied
Community Manager
January 1, 2021 – July 1, 2021
New Delhi, Delhi, India
Developer Student Clubs Adgitm
Lead
July 1, 2020 – August 1, 2021
New Delhi, Delhi, India
Deterministic Algorithms Lab
Research Intern
June 1, 2020 – August 1, 2020
Delhi, India
Skillenza
Datathon Finalist
August 1, 2019 – August 1, 2019
Banglore
DataQuestML
Founder and Speech Researcher
July 1, 2019 – June 1, 2021
Delhi Area, India
cataract-classification
October 25, 2024 – October 25, 2024
Classifying cataract images on kaggle dataset
View ProjectYolo-Scale-Tracking
October 24, 2024 – October 24, 2024
A project of using yolo model to scale on multiple Video Streams
View ProjectTrinetra
September 29, 2024 – September 29, 2024
A End to End Computer Vision Engine for Deep Learning Related Tasks
View ProjectAwesome-Projects
April 22, 2023 – April 26, 2023
Contains new and awesome computer vision application projects
View Projectfast-facenet-at-oneshot
May 13, 2019 – June 23, 2019
This project is an implementation of Siamese Neural Networks
View ProjectInferrential Statistics
Coursera
June 25, 2026 – Present
Data Science Methodology
Coursera
June 25, 2026 – Present
Applied Data Science Capstone
Coursera
June 25, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 25, 2026 – Present
Basic Statistics
Coursera
June 25, 2026 – Present
Data Analysis
Coursera
June 25, 2026 – Present
What is Data Science
Coursera
June 25, 2026 – Present
Sequence Models
Coursera
June 25, 2026 – Present
GCP Essential
Qwiklabs
June 25, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 25, 2026 – Present
Generative AI for Everyone
Coursera
June 25, 2026 – Present
Data Visualuzation
Coursera
June 25, 2026 – Present
Open Source Tools For Data Science
Coursera
June 25, 2026 – Present
Convolutional Neural Networks
Coursera
June 25, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 25, 2026 – Present
Cultural Fit Analysis
The candidate shows a strong inclination towards personal projects in AI/ML and Computer Vision, which aligns with an innovative and self-driven culture. However, the lack of team-based projects or detailed descriptions makes it difficult to fully assess collaboration and broader cultural fit. The project diversity is good within the AI/ML domain, but lacks breadth in other software engineering aspects.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. Project descriptions are minimal, and no psychometric test results are available.