About

Hasan Rafiq is a highly experienced Machine Learning Engineer at Google AI with over 11 years of industry experience in multiple regions such as AMER, EMEA, and JAPAC. He is currently leading complex cognitive business process automations through large scale ML implementations and responsible for technical solutioning/implementation of ML and AI solutions at scale. Hasan is well versed in building high-performance ML solutions on Cloud and On-premise environments on BigData scenarios for structured and unstructured data. He has in-depth expertise in driving technical implementations on Google cloud platform/AWS and is involved in imparting ML/AI and Cloud Engineering skills through various initiatives across various verticals. Hasan is a Google Certified Professional Machine Learning Engineer and a Google Certified Professional Data Engineer. He has deep learning and machine learning experience in Cloud Systems design, ML models on Terabyte scale, Scaled ingestion, batch and online pipelines, MLOps and ML Frameworks such as Tensorflow 2+, PySpark 2.4+, TFX, TF WIT, Keras, SKLearn, Airflow, and more. He has also built Deep nets (MLP, AutoEncoder, GAN, Seq2Seq) with Tensorflow, TF Keras, embedded feature engineering, and Reinforcement learning (DQN, A2C, Q-Learning with Keras) - Custom environment, OpenAI gym. Hasan has experience in Data exploratory analysis in Pandas, Seaborn plots, Facets, outlier analysis, Feature engineering such as Feature crosses, scaling, binning, Hashing trick, Embeddings, Classic ML such as Rforest, GLMNet, XGBoost: Tuning, hyperparameterization, and k-cross validations, and Model study such as PDP, Local explanations, Global explanations, isolation study. He has a good grasp of BigData and related tools like BigQuery SQL, BigQuery migration, DataPrep on Dataflow, Dataproc, GCS, Orchestration & serverless execution pipelines with Cloud Composer, Cloud Functions and PubSub, Vertex AI - Pipelines, Kubeflow, AutoML, Vizier, Workbench, ML pipeline setup and train using AI Platform, AutoML, BQML, CMLE based packaged TF models, and App engine standard & custom docker deployment with autoscale or standard machines. Currently, Hasan is working at Deloitte as a Machine Learning and Cloud Architect | Sr. Consultant, where