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machine learning @ amazon
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AWS
Machine Learning Engineer
June 13, 2026 – Present
cs336
January 7, 2026 – Present
My assignments and notes of Stanford CS336: Language Modeling from Scratch (Spring 2025)
View Projectgrok-llms
September 30, 2025 – September 30, 2025
A personal research log to learn and implement the core concepts behind large language models
View Projectinference-bench
September 21, 2025 – September 22, 2025
inference-bench — GitHub repository
View Projectgrok-ml-dl
August 28, 2025 – August 28, 2025
A personal worklog as I learn and implement the core concepts behind machine/deep learning
View Projectlearn-basics-ml-datascience
July 7, 2024 – August 6, 2024
Simple implementation of popular algorithms and techniques in machine-learning and data-science
View Projectfinetune-evaluate-codestral
June 18, 2024 – June 18, 2024
Different approaches for finetuning, evaluating, optimizations for code generation model - codestral
View Projectlearn-guardrails-for-llms
April 18, 2024 – April 18, 2024
Learning all about guardrails. ex: guardrails with bedrock, nemo, guardrails-ai and so on.
View ProjectCultural Fit Analysis
The candidate shows a strong inclination towards self-directed learning and exploration in the ML/LLM domain, which could indicate a proactive and curious mindset. However, the projects are exclusively personal and lack diversity in team collaboration or real-world business impact, which might suggest a need for more experience in collaborative, production-oriented environments. The experience level is listed as 0, despite a current role at AWS, which creates an inconsistency. The projects are highly focused on LLMs, which aligns with the target role but might indicate a narrower breadth of experience in other ML sub-fields.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The provided assessment scores for English and Psychometric tests are 0, indicating no completed tests or scores available for these areas.