Faizy Ahsan
Verified Expert in Engineering
Generative Artificial Intelligence (GenAI) Developer
Montreal, Canada
Toptal member since August 24, 2026
He is a senior machine learning engineer with over six years of experience in distributed data processing and production-scale ML systems. His expertise spans Databricks, AWS, and Docker for aerospace, adtech, and healthcare industries. At Pratt & Whitney Canada, Faizy architected and led the modernization of ML infrastructure, reducing model deployment time by 60%.
Portfolio
Experience
- Generative Artificial Intelligence (GenAI) - 6 years
- XGBoost - 5 years
- MLflow - 5 years
- Large Language Models (LLMs) - 4 years
- PySpark - 3 years
- Azure DevOps - 3 years
- Databricks - 3 years
- Kedro - 3 years
Preferred Environment
Databricks, Azure DevOps, Docker, Jenkins, Git, Agile
The most amazing...
...ML system I've built achieved over 97% accuracy in pain-score prediction from blood samples, serving real-time inference at production scale.
Work Experience
ML Specialist, MLOps Engineer
Pratt & Whitney Canada
- Architected and led ML infrastructure modernization on Databricks and Azure DevOps, building scalable MLOps and data pipelines for real-time aircraft engine analytics using PySpark and Spark SQL.
- Built Kedro-based pipeline orchestration integrated with MLflow for experiment tracking, model versioning, and automated deployment, reducing model deployment time by 60%.
- Designed end-to-end data-quality and pipeline-validation frameworks, ensuring reliability of production ML inference across distributed Databricks environments. Instrumented monitoring of model and data health.
- Developed a RAG-powered AI assistant on Amazon Bedrock, Nova, for internal knowledge management, taking an LLM application from prototype to production delivery.
- Partnered with aerospace engineers and data scientists to translate complex business requirements into scalable data architecture, communicating results to technical and non-technical stakeholders.
Senior Machine Learning Engineer
Solutions Alleviate Inc.
- Led end-to-end design and deployment of a production ML system achieving over 97% accuracy in pain-score prediction from blood samples, owning the full lifecycle from data ingestion to real-time inference.
- Architected MLflow/Docker-based inference pipeline on AWS (EC2, S3) serving PyTorch deep learning and Graph Neural Network models for real-time predictions at production scale.
- Implemented automated data-quality and validation pipelines ensuring integrity across distributed data sources and model inputs throughout the ML lifecycle.
- Led distributed execution across research partners, legal, and stakeholders.
NLP Engineer
Scribendi Inc.
- Optimized transformer models (BERT, RoBERTa, GPT, ALBERT) for production deployment for grammatical error correction via distillation and pruning.
- Achieved 35% faster inference and 40% smaller models with only 10% accuracy trade-off.
- Published two tech articles on Scribendi.ai, one describing the use of transformer-based models for grammatical error correction and the other on model compression techniques using distillation and pruning.
ML Consultant
SourceKnowledge
- Architected a RTB ML decisioning system on AWS (EC2, Redshift, Redis) processing high-volume streaming behavioral data with XGBoost and feature hashing at sub-second latency real-time.
- Designed and maintained large-scale ETL/feature pipelines with automated monitoring and data-quality checks across multiple 3rd-party data sources.
- Leveraged XGBoost, AWS (EC2, Redshift, Redis), Python, streaming data, ETL pipelines, and Django.
Experience
HR-RAG Assistant
https://github.com/drfaizyahsan/hr-rag-assistantExpected Value Router AdTech
https://github.com/drfaizyahsan/expected-value-router-adtechEducation
PhD in Computer Science
McGill University - Montreal, QC, Canada
Master's Degree in Computer Science
McGill University - Montreal, QC, Canada
Bachelor's Degree in Computer Science and Engineering
IIT Jodhpur - India
Skills
Libraries/APIs
PySpark, XGBoost, TensorFlow, PyTorch, CatBoost, Pydantic, REST APIs
Tools
Spark SQL, Jenkins, Git
Languages
Python, Java, SQL
Frameworks
Kedro, Apache Spark, Hadoop, Django, LightGBM
Paradigms
Azure DevOps, Agile
Platforms
Databricks, Docker, Kubernetes, Google Cloud Platform (GCP), Ollama, OpenShift
Other
MLflow, Large Language Models (LLMs), Generative Artificial Intelligence (GenAI), RAG Pipelines, Vector Databases, FastAPI, Machine Learning, Model Evaluation, Statistical Modeling, Machine Learning Operations (MLOps), Model Deployment, Model Monitoring, Model Tuning, CI/CD Pipelines, Personalization, Recommendation Systems, Embeddings from Language Models (ELMo), LangChain, Neural Network Pruning, Black Duck, FAISS, Delta Lake, PDMA, Applied Machine Learning, Transformer Models, Model Compression, Distillation, Quantization, Amazon Nova, PDM, GitHub Actions, RAGAS, Transformers, Computer Science
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