
As an AI/ML Engineer, I developed innovative solutions that deliver measurable impact. I created a Question-Answer generation system using LangChain and FastAPI, cutting 40 hours of manual work each month. I also designed and implemented an MLOps pipeline that enhanced computer vision models, achieving a 6x improvement in performance and a 4x increase in detected classes, ensuring the system scales reliably.
I’m passionate about solving real-world challenges through AI. One of my key projects involved designing a proof of concept for accurate exam assessments. By processing audio and video streams together, I helped improve exam integrity, offering a seamless way to verify both streams concurrently.
In a previous role as a Data Scientist, I led the development of an MLOps pipeline that reduced API calls by 90%, making the system more efficient and enabling real-time updates on training progression. I also applied deflectometry to detect surface defects in production, cutting manual labor time by 50%.
As a mentor, I've had the pleasure of working with interns and junior engineers to help them develop their skills and knowledge. I believe that mentoring is an essential part of any engineer's career, and I'm committed to paying it forward by sharing my expertise with others.
I've also had the opportunity to collaborate with frontend and robotics teams on various projects. This experience has taught me the importance of effective communication and collaboration in achieving project goals. I believe that a strong team is essential for success, and I'm always looking for ways to improve our team's dynamics and productivity.
Machine Learning Engineer
Examroom.aiMachine Learning Engineer
Lincode.aiData Scientist
Huawei TechnologiesComputer Vision and Deep learning Engineer
Cloudadic
PyTorch

MLflow

Sklearn

Mediapipe

HuggingFace

LangChain

OpenAI

Mistral

Llama

AWS

GCP

Kubernetes

Terraform
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Docker

AWS Rekognition

AWS Lambda

Python

Java

C/C++

SQL

PostgreSQL

Redis

MongoDB

Pinecone
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FastAPI

Django
Celery