Hugging Face

Democratizing good machine learning, one commit at a time.

Hugging Face is home to more than 50.000 organizations pushing ML & AI to the next level. We currently host 500k+ ML models and we are proud creators and supporters of the following open source libraries:

- transformers
- PEFT
- TRL
- datasets
- evaluate
- lighteval
- nanotron
- datatrove
- autotrain
- diffusers

We raised $395M from Sequoia, Coatue, Lee Fixel, Lux, Betaworks, the first investors at Instagram & Snapchat and Salesforce Ventures.

As part of Hugging Face I'm currently developing and growing the following products and initiatives:

- Inference Endpoints
- Hugging Face on AWS & AWS SageMaker
- GCP & Vertex AI
- Hugging Face on Azure
- NVIDIA DGC / NVCF Serverless Training

Keywords: Docker, Kubernetes, AWS, AWS SageMaker, Transformers, PyTorch, Unit Testing, CICD, Large Language Models, Generative AI, Machine Learning Engineering, FastAPI, ReactJS, Svelte

ML & Software Engineer

weet.ai

I have helped many companies understand, fine tune and deploy their Large Language Models and Gen AI applications following Software Engineering, MLOps and LLMOps best practices.

My biggest learning during this journey was that companies face both technical and business challenges when trying to leverage Generative AI and Large Language Models.

This was my biggest motivation for starting weet.ai: helping companies navigate this complex landscape and unlock unique use cases powered by Generative AI.

Keywords: Python, PyTorch, Generative AI, LLMs, MLOps, Machine Learning Engineering, Artificial Intelligence, LLMOps, Kubernetes, MLflow, Weights & Biases, Hugging Face, Docker, FastAPI, Terraform, Azure, AWS, GCP, Apache Spark, Apache Kafka, ReactJS

Principal Machine Learning & AI Engineer

LLMs HowTo

LLMs HowTo aims to bridge the gap in Generative AI and Large Langugage Models by demistifying business cases and recent developments in the field.

Master of Disaster

O'Reilly

Technical reviewer for the upcoming book "Hands-on Large Language Models"

Technical Reviewer

Databricks

As a Specialist Solutions Architect, I have a heavy hands-on focus on helping customers achieve the best outcomes from AI and Machine Learning. Specialties:

- MLOps
- Machine Learning Engineering
- Deep Learning
- Computer Vision
- Natural Language Processing
- Natural Language Understanding
- Large Language Models (LLMs)
- Generative AI

In terms of tech stack, my work usually entails:

- PyTorch
- PyTorch Lightning
- Hugging Face
- MLflow
- Apache Spark & SparkML
- Apache Kafka
- Scikit-Learn
- Terraform
- Petastorm
- Horovod
- Deepspeed
- FastAPI
- Kubernetes

Specialist Solutions Architect AI & Machine Learning

With origins in academia and the open source community, Databricks was founded in 2013 by the original creators of Apache Spark™, Delta Lake and MLflow. 

As the world’s first and only lakehouse platform in the cloud, Databricks combines the best of data warehouses and data lakes to offer an open and unified platform for data and AI. Curently, I work as part of a brilliant team of Solution Architects covering the UK, Ireland and Benelux regions.

Main objectives:

• Consult on architecture and design, bootstrap, and/or implement strategic customer projects
• Build references architectures, how-tos, and demo applications for customers
• Architect, implement, and/or validate integrations with 3rd party applications 
• Evangelize Spark, Databricks, Machine Learning and MLOps across developer community through meetups and conferences 
• Act as a Subject Matter Expert on topics such as Machine Learning, MLOps, Machine Learning Engineering etc. 

Keywords: Data Engineering, Machine Learning Engineering, Solution Architecture, Azure, AWS, PySpark, Scala, Spark Structured Streaming, Confluent Kafka, Amazon MSK, Delta Lake, Kubernetes, Terraform, Databricks Machine Learning, MLflow, PyTorch, PyTorch Lightning, Horovod, Petastorm, Transformers, Hugging Face

Solutions Architect Data & AI

At ING, I was part of the Global Customer Dialogue Analytics CoE. 

My role was to leverage my Data Science, Data Engineering, Machine Learning Engineering, Large Language Models (LLMs) and Solution Architecture skills in order to deliver the customer service of the future.

Keywords: Data Engineering, Python, Docker, Kubernetes, OpenShift, Helm, Apache Airflow, Machine Learning Engineering, MLOps, Natural Language Processing (NLP), CICD, Chatbots, Automatic Speech Recognition (ASR), Tensorflow, PyTorch, Hugging Face, Kaldi, Named Entity Recognition (NER), Sci-Kit Learn, spaCy, Postgres, LLMs

Senior Machine Learning Engineer

ABN AMRO Bank N.V.

As part of Chief Architecture and Data Management team, my role was to architect and implement a bank wide Data Orchestration Platform based in Apache Airflow. 

This was structured as a PaaS offering on top of Kubernetes, so that multiple domain data stores within ABN could onboard their orchestration workloads in a seamless manner. This was a critical step in the road towards the implementation of a Data Mesh architecture.

Consulting assignment through Altius/Avanade.

Keywords: Azure, Python, Data Engineering, Databricks, Docker, Kubernetes, Helm, Pyspark, Apache Airflow, CICD, Hashicorp Vault, Data Mesh

Data Engineer

Ahold Delhaize

At Albert Heijn my role was to create an Enterprise Data Lake for customer data, which allowed data scientists, data analysts, marketers and other business users to unlock unique business insights and opportunities.

Consulting assignment through Altius/Avanade.

Keywords: Azure, Delta Lake, Data Lake, Data Engineering, Databricks, Python, Apache Spark, Pyspark, Hashicorp Terraform, Infrastructure as Code, CICD

Vattenfall

Worked as a consultant within the Renewable Energy Forecasting and Optimization department in Hamburg, Germany, where my main objective was to create a streamlined, realtime data platform based in microservices, with the focus of taking the Digital Power Purchase Agreement (PPA) - day-ahead and intraday energy trading business to the next level

Consulting assignment through Sia Partners.

Keywords: Azure, Python, Docker, Kubernetes, Machine Learning, Sci-Kit Learn, Gradient Boosted Decision Trees, LightGBM, CICD, DevOps

Bradesco

Managed IT products in order to implement digital change and transformation within Private Banking and Foreign Exchange departments in Argentina, Luxembourg, Cayman Islands and New York.

Product Manager FX & Private Banking IT

Gen AI | LLMs | Machine Learning Engineering | AI Engineering | Azure | AWS | CKAD | MLOps | LLMOps

I have a strong background in software engineering, cloud architecture, solution architecture, machine learning engineering, generative AI, large language models, and MLOps.

I'm passionate about leveraging these and other skills to conceptualize and deliver complex and cutting-edge data and AI solutions that provide business value and unlock unique opportunities. 

I am a huge believer of teamwork, autonomy, accountability, user-centricity, and data-driven decisions. I am passionate about learning new technologies and advancing the state of the art in data and AI.

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