Assaf Pinhasi consulting

Helping companies build real-world, ground-breaking Data and Machine Learning-based products:

🎯 Data infra and pipelines - Collection, storage, data modeling

🎯  ML research lifecycle  - Streamlining and making research reproducible

🎯  Production ML pipelines - Automating model retraining, testing and deployment

🎯  Inference and operations - Serving models at scale, monitoring and improving over time


A typical project includes two phases:

✅   Architecture - specification, system design, technology selection, planning and de-risking
✅   Implementation - Building systems and guiding organic teams in adopting and extending them
 
Technologies: 

✅   Python, Cloud (AWS/GCP), PyTorch ecosystem
✅   Spark, Airflow, Prefect, Kafka, PubSub, NoSQL DBs
✅   Docker, Kubernetes, serverless and all things distributed 
✅   MLOps tooling: From managed to open-source to building tools in-house, I've worked with many

MLOps, ML engineering and data hands-on architect (consulting)

The Apache Software Foundation

Apache Liminal (incubating)  helps teams orchestrate their machine learning pipelines by formalizing the ML system's design, and allowing DS and Engineering teams to effectively collaborate on building it together.

PPMC member, Apache Liminal (Incubating)

Zebra Medical Vision Ltd

Leading the R&D as we are building a Deep Learning based system for detecting important and life-saving findings in medical images such as CT, X-ray and more. 

System is deployed in multiple hospitals globally and impacting patient care.

🎯  Building a portfolio of Deep Learning products from idea to production and operations

🎯  Hiring the majority of the team (35 strong), org structure, forming R&D leadership.
 
🎯  Leading the Deep Learning team directly for 18 mo., guiding research, growing the team X4

🎯  Owning the company's production system (on premise + cloud), architecture to operations

🎯  Creating DL infra - Compute/storage, training clusters, Pipeline FW, experiment tracking

🎯  Building peta-scale data platform - acquire, de-identify, clean, store, index, and warehouse.


Technology domains: 

AI, Deep Learning, Computer Vision, Machine Learning, Analytics, Natural Language Processing (NLP), Big Data engineering, DevOps, QA automation, Full stack, micro-services, Cloud

Technology stack: 

✅   Python, TensorFlow, keras
✅   Redis, elasticsearch, mongoDB
✅   Docker, Kuberentes , rancher
✅   Node.js, postgres, angular
✅   AWS, custom data-center technologies

VP R&D 

PayPal

Creating a group in charge of a new Big Data Platform for PayPal's Risk org. 
The platform enabled PayPal engineers and scientists to author data pipelines combining
Stream and batch processing.

Platform included Infra, SDK, QA and and DevOps Tooling.

🎯  Going from initial idea to running production apps, in a short time

🎯  Enabling multi-million USD business through the products which run on the platform

🎯  Driving the adoption of Stream processing at PayPal - from architecture to production

🎯  Hiring and building a group of top-notch engineers and leaders

🎯  Contributing to Apache Beam open source project (Committee members and committers)

Technology stack: 

✅   Java, Scala, SQL
✅   Spark, Spark Streaming, Apache Beam, Kafka, Aerospike
✅   Elastic Search, Graphite, Grafana, ELK and more...

Director, Big Data Platform

Created and Led Risk's Advanced Analytics Data Engineering group, delivering large scale 
fraud-prevention and behavioral analytics data products. 

🎯 Shaping Risk decisions and user experience of PayPal's 200+ million active customers.

🎯 Working with Data science teams from problem statement to production and maintenance

🎯 Creating complex Hadoop jobs, running on Petabytes of storage and 1500+ nodes

🎯 Hiring, training and mentoring the majority of the developers and managers globally

Technology Domains: 

Big Data, Graph processing, Crawling, Text mining, Natural Language processing (NLP), Data Science, Analytics, Machine Learning

Technology stack: 

✅  Hadoop, pig, hive, 
✅  Data warehousing, ETL, SQL
✅  Java, Spring
✅  And more...

Sr. Manager, Big Data Engineering group leader

Big Data Engineering Team Leader

Pontis (later acquired by Amdocs)

🎯  Co-creating the company's internal platform - on which the entire product portfolio is built
🎯  Owning the Persistence, Web Service, and Data Migration Frameworks
🎯  The senior authority on OS technologies

Technology stack: 

✅ Spring, Java, JEE,  Hibernate
✅ Oracle, MySQL, DSL's

Senior Software Architect

Pontis

Software Engineer

Commtouch

Detecting security threats using data mining and analytics.

Technology stack: 

✅ SQL, Data modeling
✅ Python
✅ ML model training and evaluation

Lead Data Scientist / Analyst (internet security)

IDF - 8200

Intelligence Officer (HAMAN TALPIOT)

Technologist and leader, specializing in Data intensive and Machine Learning systems. 

Currently providing *hands-on architect* consulting and development services.

I enjoy solving complex, multi-disciplinary challenges and delivering high quality bespoke solutions.

Technologies and skills:
- Machine Learning Engineering - Engineering ML systems ( classical ML, Deep Learning, genAI)
- MLOps - Setting up ML infrastructure and processes for fast, safe and tractable iterations
- Data engineering - Collecting, moving, processing, modeling, storing and analyzing data at scale
- Backend, Frontend and more...

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