Open to opportunities

Adil Shamim

@adilshamim

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Machine Learning Engineer building production ML systems, MLOps pipelines, and impactful recommender solutions.

Bangladesh

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What I'm looking for

I seek roles where I can build production ML systems and MLOps pipelines, deliver measurable product impact, and work in collaborative, execution-focused teams.

I am a Machine Learning Engineer with 2+ years building production systems, Dockerized inference services, tracked experiments, and ML products teams use.

I founded Toolly, a live AI tools platform with 400+ tools and a Learn AI hub, and engineered the full product stack and deployment workflows solo.

I published a first-author conference paper on Bengali speaker diarization achieving a 56% inference speedup, and I rank in the Top 1% on Kaggle with multiple competition results and open-source contributions.

I deliver production-grade pipelines and services—ZenML, MLflow, Docker, FastAPI—focused on reproducibility, deployment, and measurable business impact, such as a recommender that lifted client sales by 10% in 90 days.

Experience

Work history, roles, and key accomplishments

Current

Founder & Full-Stack ML Engineer

Current

Toolly

Jun 2025 - Present (9 months)

Architected and launched toolly.tech solo, a live AI tools directory of 400+ tools and integrated Learn AI hub; implemented submission, moderation, search, and analytics and shipped Toolly Studio (Streamlit + Bria AI) with Docker deployment.

Python Streamlit Docker fastAPI Search Analytics Deployment

Machine Learning Engineer (Kaggle Competitor)

Kaggle / GitHub

Ranked top 1% in competitions (e.g., Predicting Road Accident Risk) and completed 22 competitions while publishing notebooks and datasets to engage the data-science community.

Python XGBoost LightGBM scikit learn Model Evaluation Notebooks Open Source

ML Engineer — Prices Predictor System

Personal Project

Built an end-to-end production ML pipeline using ZenML and MLflow, trained XGBoost/LightGBM models, and deployed a Dockerized FastAPI inference service with CV and hyperparameter tuning.

ZenML MLFlow XGBoost LightGBM Docker fastAPI CI CD Hyperparameter Tuning

Freelance Machine Learning Engineer

Self-employed

Built and deployed a hybrid recommendation system (ALS + TF-IDF embeddings) with a Flask API that produced a 10% sales lift for a local client within 90 days.

Python Flask Collaborative Filtering TF IDF Recommendation Systems Deployment Docker A B Testing

Research Author — Speaker Diarization

BUET CSE Fest

Published first-author paper on Bengali speaker diarization; fine-tuned segmentation and replaced embeddings to achieve a 56% inference wall-clock speed improvement and competitive DER on benchmarks.

Speaker Diarization Model Fine Tuning WeSpeaker ResNet34 LM Deep Learning TensorFlow Evaluation