Senior AI Engineer @ cander | Top AI Voice | Building Production-Grade GenAI Systems | LLMs | RAG | MLOps | AWS | GCP | Azure | Agentic AI Workflows
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SmolLM2-360M-Instruct-Text-2-JSON
April 18, 2025 – June 21, 2025
A fine-tuned version of SmolLM2-360M-Instruct-bnb-4bit specialized for parsing unstructured calendar event requests into structured JSON data.
View Projectskills-build-applications-w-copilot-agent-mode
April 8, 2025 – April 8, 2025
Exercise: Build my application with Copilot agent mode
View ProjectTextleap-AI-Privacy-Policy
December 23, 2024 – January 15, 2025
Textleap-AI-Privacy-Policy — GitHub repository
View ProjectChar-isma
October 12, 2024 – October 27, 2024
Char-isma is an Autoregressive Character-level Language Model.
View ProjectAutomated-Course-Content-Generator
May 13, 2024 – February 16, 2025
Automated Course Content Generator (ACCG) is an AI-powered Streamlit app for SMEs, Content Creators, and Educators. Input Course Name, Audience Level, Difficulty, and Credits to get a dynamic course outline, full course content, and quizzes. Download everything as a PDF, PPT and customize as needed!
View ProjectDepression-Detection-Digital-Assistant-RoBERTa
April 24, 2024 – August 11, 2024
Developed an automated system to detect signs of depression from digital data using the Hugging Face's roBERTa-base model from the transformers library in Python, achieving a 89.18% accuracy. Deployed the model in a Flask-based application for real-time analysis.
View ProjectAI-News-Companion
March 2, 2024 – April 20, 2025
This Streamlit application serves as a News Search Agent. I call it Newzy. The agent is capable of providing the latest news, along with links to relevant articles, and summarize the news based on the user's search query.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and demonstrate a strong interest in AI/ML, particularly in NLP and generative AI. The diversity of projects, from content generation to depression detection and news summarization, shows a broad curiosity within the AI domain. The target role is MLOps, and while the candidate has strong ML development skills, there is limited explicit evidence of MLOps practices (e.g., CI/CD, monitoring, scalable deployment, infrastructure management) in the project descriptions. This suggests a potential gap in direct alignment with the operational aspects of MLOps, though the ML development background is a strong foundation.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-directed approach to learning and application development. The focus on building functional applications suggests a results-oriented mindset. However, without formal work experience or psychometric test results, it is difficult to assess stress handling, team collaboration, or other operational fit aspects.