I make learning Data Science effortless for you | Data Science @ Bosch

Hi 👋🏻
I'm Banias, AI Engineer at Netze BW.

Applying new technologies and methods in Data Science & AI is my passion.

Through my experience and continual learning, I've gained valuable insights and tips that I love sharing with Data Scientists, Machine Learning Engineers and builders like you.

If you're looking for practical advice, helpful resources, and articles on the latest trends or best practices in the field, you're in the right place.

Let's connect and stay updated on the exciting world of Data Science together. Feel free to reach out, read my articles, and let's grow our knowledge and network. :)


Note: My views are my own and don‘t represent my employer.

Banias Baabe

Most people running local AI models have no idea which ones will actually work on their hardware.

𝗹𝗹𝗺𝗳𝗶𝘁 is a small open source CLI tool that scans your system and tells you exactly which models fit your setup.

No more downloading files that turn out to be too large to run.

Here is what it does:
✅ Evaluates 150+ models from 30 providers against your CPU, GPU, and RAM specs.
✅ Returns a ranked list of models that match your hardware.
✅ Connects with Ollama and LM Studio to detect and download models directly.
✅ Supports multi GPU setups and Mixture of Experts architectures.

It's a simple quality of life tool that saves real time for developers working with local AI.

🔗 Link to repo: github(.)com/AlexsJones/llmfit


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I teach AI Engineers the concepts and tools they need to stay ahead | AI Engineer @ Netze BW

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

I build and ship production AI systems.

My approach combines deep technical execution with strategic thinking: from deploying enterprise LLM infrastructure at scale to teaching Production AI Agents to engineers at Meta, NVIDIA, TD Bank, Nubank and other major financial institutions.

I thrive at the intersection of cutting-edge AI and real-world constraints - making agents work in production, optimizing for cost and latency, and building systems people actually want to use.

Core capabilities: Agentic systems architecture, production LLM deployment, MLOps/LLMOps, customer-facing technical leadership

Current stack: Python, OpenAI Agents SDK, LlamaIndex, Haystack, Phoenix Arize, MLflow, React/TypeScript, Terraform, Kubernetes, Vector DBs (Azure AI Search, Qdrant), PyTorch, Apache Spark, React, Typescript, VueJS, Terraform

Apart from my 15+ years delivering cutting edge tech in banking and financial markets, I scaled global training and inference infrastructure at Hugging Face and consulted Fortune 500s on ML and AI platforms at Databricks.

I believe the best AI systems emerge from tight feedback loops with users, rigorous experimentation, and teams that share knowledge freely. Always learning, always shipping.

🚀 Rafael V. Pierre, MSc.

Excited to share that I've just joined Citi as Lead AI Engineer in FX Data and AI -  and yes, I've also just moved to London, so I'm navigating two new systems simultaneously (the role and the Tube).

After 17 years across HSBC, ING, Databricks, Hugging Face and ABN AMRO Bank N.V., this is an exciting new chapter. There are few markets that generate data at the scale and velocity of FX - and the AI potential there is still largely untapped.

Relocating from the Netherlands with me is Charlie, who has opinions about the move. As you can see, she's reviewed my home office setup and is not fully convinced.

If you're also based in the UK and working at the intersection of finance and AI, I'd love to connect. Strong opinions on London parks and Canary Wharf restaurants also welcome - as well as dog walker recommendations

🚀 Rafael V. Pierre

⚡️ AI & Agents Tech Lead | ex 🤗 Hugging Face, Databricks | Weekly AI Insights at lighthousenewsletter.com

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