Joydeep Tripathy

ML Engineer

https://talent.gravityer.com/joydeep-tripathy

Key Strengths

Strong foundational knowledge in Machine Learning and Deep Learning, demonstrated through personal projects like 'Dynamic Image Styler' and 'StarFace Creator'.
Practical experience with advanced ML techniques such as Probabilistic Modelling, KL-Divergence Loss, Deep Conditional Convolutional Generative Adversarial Networks (DCC-GAN), and quantization techniques (Activation-Aware Quantization, AQLM).
Experience in optimizing ML models and training processes, including model efficiency improvements (80%), TPU distribution strategy for scalability (90%), and pipeline decoupling for faster component extraction.
Internship experience at reputable organizations like Google Summer of Code (OpenSSF) and Nyun AI, directly relevant to ML Engineer role.
Demonstrated ability to contribute to open-source projects and take on maintainer duties, indicating strong ownership and collaboration skills.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's involvement in open-source (Google Summer of Code) and diverse ML projects (image styling, celebrity generation, quantization research) indicates a proactive and curious individual. Their experience aligns well with a culture that values innovation, continuous learning, and practical application of advanced ML concepts. The internships suggest an ability to adapt to different organizational structures and contribute effectively. However, the experience level is entry-level, which might require more mentorship in a senior role.

Soft Skills & Operational Fit

The candidate's experience at Google Summer of Code, where they contributed to CVE-Binary-Tool and took over maintainer duties, suggests strong initiative, problem-solving, and a collaborative mindset. Their focus on optimizing processes and improving efficiency in projects indicates a results-oriented approach. However, without specific psychometric or English test scores, a comprehensive assessment of communication, stress handling, and team collaboration is limited.

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About

AI Researcher, Open-Source Contributor and Maintainer. On the Engineering side, I mostly work with backend systems with special interest in network and OS related problems. On the Deep Learning side, my major area of interest is Generative Models: Auto-Regressive, Latent-Variable, Energy-based, Score-based and GANs. Coming to Open-Source, I contribute to and maintain CVE-Binary-Tool - previously backed by Intel and currently backed by OpenSSF. Also contributed to other Open-Source projects.

Top Skills

Neural NetworksDjangoGenerative AiScikit LearnMatplotlibPandasNumpyData AnalysisMachine LearningPyTorchTensorFlowDeep LearningHTML5C++Core Java

Education

Vidya Bharti Chinmaya Vidyalaya, Jamshedpur

Higher Secondary

January 1, 2020 – January 1, 2022

ABV-Indian Institute of Information Technology and Management

Bachelor of Technology - BTech, Computer Science

N/A – Present

Experience

HackerRank

SDE Intern

January 1, 2026 – June 1, 2026

Bengaluru · On-site

Google Summer of Code

Student Contributor

May 1, 2025 – September 1, 2025

Remote

Nyun AI

Machine Learning Engineer Intern

February 1, 2025 – March 1, 2025

Remote

YahWeh Innovations

Machine Learning Engineer Intern

July 1, 2024 – December 1, 2024

Remote

Projects

StarFace Creator

July 1, 2023 – August 1, 2023

· Created A Celebrity Image Generator Using Deep Learning. · Utilized Deep Conditional Convolutional Generative Adversarial Network (DCC-GAN) to achieve this. · Optimized training using TPU distribution strategy, significantly accelerating the process and enhancing scalability by over 90%.

Dynamic Image Styler

January 1, 2023 – February 1, 2023

· Used Probabilistic Modelling to Dynamically Style Images Using Tensorflow. · Successfully added and implemented KL-Divergence Loss Into the Application. · Applied Various optimizations to improve the model efficiency by over 80%.

Key Strengths

Strong foundational knowledge in Machine Learning and Deep Learning, demonstrated through personal projects like 'Dynamic Image Styler' and 'StarFace Creator'.
Practical experience with advanced ML techniques such as Probabilistic Modelling, KL-Divergence Loss, Deep Conditional Convolutional Generative Adversarial Networks (DCC-GAN), and quantization techniques (Activation-Aware Quantization, AQLM).
Experience in optimizing ML models and training processes, including model efficiency improvements (80%), TPU distribution strategy for scalability (90%), and pipeline decoupling for faster component extraction.
Internship experience at reputable organizations like Google Summer of Code (OpenSSF) and Nyun AI, directly relevant to ML Engineer role.
Demonstrated ability to contribute to open-source projects and take on maintainer duties, indicating strong ownership and collaboration skills.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit