Match Report
Aleksy Studnicki — AI Engineer (LLM / Generative AI) at Unknown
Global Score
41%
Detailed Score
28%
Final Score
13%
Python programming
must haveSterke Python-kennis
Python programming
must haveSterke Python-kennis
LLM practical experience
must haveMinimaal 2 jaar praktijkervaring met LLM-toepassingen (GPT-4, Claude, Llama)
LangChain or LlamaIndex
must haveKennis van LangChain of LlamaIndex
Vector database experience
must haveErvaring met vector databases (Pinecone, Weaviate, pgvector)
Prompt engineering
must haveBekendheid met prompt engineering technieken
Azure OpenAI or OpenAI API
must haveKennis van Azure OpenAI of OpenAI API
LLM practical experience
must haveMinimaal 2 jaar praktijkervaring met LLM-toepassingen (GPT-4, Claude, Llama)
RAG architecture experience
must haveErvaring met RAG-architecturen (embedding, vector databases, chunking)
LangChain or LlamaIndex
must haveKennis van LangChain of LlamaIndex
Vector database experience
must haveErvaring met vector databases (Pinecone, Weaviate, pgvector)
Prompt engineering
must haveBekendheid met prompt engineering technieken
Azure OpenAI or OpenAI API
must haveKennis van Azure OpenAI of OpenAI API
RAG architecture experience
must haveErvaring met RAG-architecturen (embedding, vector databases, chunking)
Agent frameworks knowledge
nice to haveKennis van agent frameworks (AutoGen, CrewAI)
Legal AI solutions
nice to haveBekendheid met juridische AI-oplossingen
Document parsing experience
nice to haveErvaring met document parsing (OCR, PDF-extractie)
LLM fine-tuning
nice to haveErvaring met fine-tuning van LLM's
Agent frameworks knowledge
nice to haveKennis van agent frameworks (AutoGen, CrewAI)
Legal AI solutions
nice to haveBekendheid met juridische AI-oplossingen
Document parsing experience
nice to haveErvaring met document parsing (OCR, PDF-extractie)
GDPR compliant AI implementation
nice to haveKennis van AVG-conforme AI-implementatie
GDPR compliant AI implementation
nice to haveKennis van AVG-conforme AI-implementatie
LLM fine-tuning
nice to haveErvaring met fine-tuning van LLM's