Arno Candel
Member Of Technical Staff at xAI
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolArno Candel is a seasoned AI engineer and technical leader with 12+ years building production-grade machine learning and generative-AI platforms, most recently as Member of Technical Staff at xAI and formerly CTO of H2O.ai. He drove development of flagship products like H2O-3, Driverless AI and the enterprise h2oGPTe platform, personally contributing tens of thousands of commits and leading wins on benchmarks such as GAIA. Trained as a physicist (PhD, ETH Zurich) with a background in large-scale MPI/C++ scientific computing at SLAC and Stanford, he brings rare expertise in high-performance distributed algorithms and GPU-accelerated ML systems. A hands-on full-stack builder, Arno has deep experience integrating LLaMA-family models, 4-bit quantization, and Flash Attention into private, production-ready inference pipelines (h2ogpt). His work spans open-source and enterprise, from pioneering scalable ML in H2O-3 to commercial AutoML and agentic GenAI, and includes pragmatic optimizations that enabled real-world deployments at scale. Based in Palo Alto, he combines research rigor with product-focused execution and an engineer’s penchant for squeezing performance from both algorithms and infrastructure.
12 years of coding experience
24 years of employment as a software developer
PhD Computational Physics, PhD Computational Physics at ETH Zürich
English, German, French, Turkish, German, Dutch
Stackoverflow
491reputation
17kreached
18answers
0questions
Github Skills (25)
transformers10
spark10
integrate10
python10
machine-learning10
pyspark10
integrations10
h2o10
huggingface10
tensorflow10
gpt10
data-integration10
word2vec9
scala9
big-data9
Programming languages (7)
Github contributions (5)
h2oai/h2ogpt
Apr 2023 - Jul 2024
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
Role in this project:
Back-end Developer
Back-end DeveloperContributions:37 reviews, 54 PRs, 445 pushes in 1 year 3 months
Contributions summary:Arno primarily worked on the `generate.py` file, modifying the base model, default parameters, and generation output. They focused on incorporating and integrating various machine learning models, including LLaMA and other models into the generation pipeline. The contributions involved setting up and configuring the generation process, with emphasis on enabling 4-bit quantization and the use of Flash Attention. The user also implemented the saving of prompt/response data to JSON files.
aichatgptembeddingsgenerativegpt
h2oai/sparkling-water
May 2015 - Jun 2016
Sparkling Water provides H2O functionality inside Spark cluster
Role in this project:ML Engineer & Data Engineer
ML Engineer & Data EngineerContributions:50 commits, 15 pushes, 1 comment in 1 year 1 month
Contributions summary:Arno contributed significantly to the project by adding and refining code related to machine learning and data processing within the context of the Sparkling Water framework. They added a new example using Word2Vec for job title analysis. Additionally, the user updated and improved an existing Deep Learning example, and implemented a distributed TensorFlow deep learning MNIST demo for PySparkling. These contributions showcase a focus on integrating machine learning techniques with Spark and H2O.
develapiintegrationrsparklingh2o
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