Khalid Salama
Senior Staff Software Engineering Manager, GenAI at Google DeepMind
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolKhalid Salama is a Senior Staff Software Engineering Manager specializing in GenAI, combining 15+ years of industry experience with a strong academic pedigree including a PhD and 30+ published research papers. He has led ML and AI teams across Google (Bard, Assistant, Cloud AI) and now Google DeepMind in Zurich, building large-scale data platforms, production ML pipelines, and MLOps solutions. Hands-on contributions to prominent open-source Google Cloud ML projects and Keras (including TensorFlow serving, estimator tutorials, and a supervised contrastive learning example) underscore his practical expertise deploying models at scale. He blends research rigor with production focus—designing feature engineering, inference pipelines, and request-response logging into BigQuery—to move models from prototype to robust services. Based between Zurich and academia as an Honorary Research Fellow, he brings both leadership of cross-functional engineering organizations and deep technical mentorship to complex GenAI initiatives.
11 years of coding experience
8 years of employment as a software developer
Master of Science (MS) Computer Science, Master of Science (MS) Computer Science at The American University in CairoBachelor of Science (BS) Information Technology, Bachelor of Science (BS) Information Technology at Ain Shams UniversityDoctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at University of Kent
English, Arabic, French
Github Skills (28)
continuous-deployment10
google-cloud-platform10
dataflow-programming10
bigquery10
data-pipelines10
dataflow10
python10
gcloud10
image-classification10
machine-learning10
ml-deployment10
data-model10
saves10
ml10
gcp10
Programming languages (3)
Github contributions (5)
GoogleCloudPlatform/tf-estimator-tutorials
Dec 2017 - Nov 2019
This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way
Role in this project:
ML Engineer
ML EngineerContributions:82 commits, 7 PRs, 67 pushes in 1 year 11 months
Contributions summary:Khalid contributed to improvements to the example, specifically to the housing price estimation, feature scaling and regression model using the TensorFlow estimator APIs. The contributions include modifications to the notebook, possibly including changes to data preprocessing, model architecture, and evaluation metrics to enhance the model's accuracy and performance. The user appears to be actively working on refining the example within the repository.
pythonsystematicdeep-learningmachine-learningtensorflow
GoogleCloudPlatform/mlops-on-gcp
Mar 2020 - Jul 2021
Role in this project:MLOps Engineer
MLOps EngineerContributions:153 commits, 28 PRs, 45 pushes in 1 year 3 months
Contributions summary:Khalid created and deployed a notebook to train and serve a TensorFlow model to AI Platform Prediction with request-response logging to BigQuery. They developed the training and serving notebook, including the setup, data preparation, model training, and deployment to AI Platform. They also enabled and configured the request-response logging to BigQuery. The user further developed code to create a BigQuery view for parsing logs.
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