Vachan

Deep learning Engineer

https://talent.gravityer.com/vachan

| Deep Learning | Compilers |

Bengaluru, Karnataka, IndiaMember since June 13, 2026

Key Strengths

Extensive personal project experience in Deep Learning, Reinforcement Learning, and Large Language Models (LLMs).
Demonstrated proficiency in PyTorch and JAX for implementing advanced neural network architectures.
Strong foundational understanding of neural networks, as evidenced by the 'NeuroForge' project.
Experience with Diffusion Models and Transformer architectures, directly relevant to Deep Learning Engineer roles.
Exposure to low-level programming (C++, Assembly) through the 'nanocc' project, indicating a broad technical curiosity.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong passion for deep learning and AI research, which aligns well with an innovative and research-driven culture. The focus on personal projects suggests self-motivation and a proactive learning approach. However, the lack of team-based projects or professional experience makes it difficult to fully assess collaboration and broader cultural fit.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

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Projects

VachanVY.github.io

January 3, 2026 – Present

hugo && cd public && git add . && git commit -m "Update site content" && git push && cd ..

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nanocc

October 12, 2025 – Present

The Nano C Compiler (nanocc)

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Reinforcement-Learning

September 5, 2024 – August 14, 2025

PyTorch implementations of algorithms from "Reinforcement Learning: An Introduction by Sutton and Barto", along with various RL research papers.

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Transfusion.torch

August 24, 2024 – October 10, 2024

PyTorch Implementation of Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

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diffusion-transformer

August 16, 2024 – June 19, 2025

Pytorch and JAX Implementation of Scalable Diffusion Models with Transformers | Diffusion Transformers in Pytorch and JAX

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VachanVY

July 13, 2024 – Present

VachanVY — GitHub repository

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gpt.jax

February 9, 2024 – October 6, 2024

Generative Pretrained Model (GPT) in JAX. A step by step guide to train LLMs on large datasets from scratch

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Rotary-Embeddings

February 4, 2024 – January 28, 2025

Simple Implementation of Rotary Positional Embeddings (RoPE) and Sinusoidal Positional Embeddings in JAX

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DETR

December 31, 2023 – March 10, 2025

Simplifying Object detection. DEtection TRansformer (DETR) in JAX.

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NeuroForge

December 31, 2023 – October 1, 2025

Unveiling the Layers: Neural Networks from first principles

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Key Strengths

Extensive personal project experience in Deep Learning, Reinforcement Learning, and Large Language Models (LLMs).
Demonstrated proficiency in PyTorch and JAX for implementing advanced neural network architectures.
Strong foundational understanding of neural networks, as evidenced by the 'NeuroForge' project.
Experience with Diffusion Models and Transformer architectures, directly relevant to Deep Learning Engineer roles.
Exposure to low-level programming (C++, Assembly) through the 'nanocc' project, indicating a broad technical curiosity.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

Vachan

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit