AI Research at Level AI. Ex- AI at @Mastercard, @Samsung Research. CS Grad, IIT (BHU) Varanasi.
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Assessing your cultural and operational fit
Level AI
Software Engineer
June 15, 2026 – Present
LLM-Sampling
September 28, 2024 – December 9, 2024
A collection of various LLM sampling methods implemented in pure Pytorch
View ProjectAttention-Mask-Patterns
September 7, 2024 – September 22, 2024
Using FlexAttention to compute attention with different masking patterns
View ProjectRed-Teaming-Language-Models-with-Language-Models
October 7, 2023 – October 9, 2023
A re-implementation of the "Red Teaming Language Models with Language Models" paper by Perez et al., 2022
View ProjectSpeculative-Sampling
September 2, 2023 – February 29, 2024
Implementation of Speculative Sampling as described in "Accelerating Large Language Model Decoding with Speculative Sampling" by Deepmind
View ProjectFlashAttention-PyTorch
June 10, 2023 – Present
Implementation of FlashAttention (FA1-FA4) in PyTorch for educational and algorithmic clarity
View ProjectExtracting-Training-Data-from-Large-Langauge-Models
July 6, 2022 – July 10, 2022
A re-implementation of the "Extracting Training Data from Large Language Models" paper by Carlini et al., 2020
View ProjectML-Optimizers-JAX
June 20, 2021 – June 20, 2021
Toy implementations of some popular ML optimizers using Python/JAX
View ProjectAnnotated-ML-Papers
April 18, 2021 – Present
Annotations of the interesting ML papers I read
View ProjectCSE241N-ArtificialIntelligenceFall18
January 16, 2018 – June 28, 2025
Official Repository for all the lab submissions of the course CSE241N-AI taken by undergraduate students at IIT (BHU), Varanasi.
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated on Large Language Models and deep learning research, which aligns well with a specialized Data Scientist role in AI/ML. The diversity of projects within this niche (attention mechanisms, sampling, security, optimization) shows a broad interest in the field. However, the lack of team-based projects or contributions to open-source beyond personal re-implementations makes it difficult to assess collaboration and broader cultural fit. The single professional experience as a 'Software Engineer' at Level AI, with a future start date, provides limited insight into past professional cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions are clear and concise, indicating good technical communication. The focus on re-implementing research papers suggests a detail-oriented and persistent approach to problem-solving. However, without psychometric or English test results, a comprehensive assessment of soft skills, stress handling, and team collaboration is not possible.