AI developer
Proxima Research
π₯
$$$$
πΊπ¦ Ukrainian Product
Tech Stack:
β Python (5+ years)
β Strong working knowledge of SQL for data extraction and analysis (3+ years preferred)
β API integration with LLMs: OpenAI, Azure OpenAI, Claude
β ML/LLM architectures: RAG, embeddings, retrievers
β DevOps/MLOps: Docker, deployment of models on dedicated servers or cloud infrastructure
β Nice to have: FastAPI, vector databases (FAISS, Weaviate), prompt engineering
β Tools under consideration: LangChain or similar frameworks for rapid prototyping of LLM-based pipelines
Responsibilities:
β Design and build a production-grade LLM+RAG system for contextual data analysis
β Integrate external data sources and tools into the assistantβs knowledge base
β Set up and fine-tune LLMs on dedicated infrastructure or in the cloud
β Develop complex multi-step agents and orchestrated pipelines
β Build integrations with different platforms via API
β Ensure performance, scalability, and CI/CD automation of the ML systems
Requirements:
β Proven experience building real-world AI/ML products
β Deep understanding of the full machine learning lifecycle
β Experience working with popular LLM APIs and frameworks
β Ability to work independently and propose technical solutions
β Hands-on experience with LLM+RAG design patterns and prompt engineering
β Python (5+ years)
β Strong working knowledge of SQL for data extraction and analysis (3+ years preferred)
β API integration with LLMs: OpenAI, Azure OpenAI, Claude
β ML/LLM architectures: RAG, embeddings, retrievers
β DevOps/MLOps: Docker, deployment of models on dedicated servers or cloud infrastructure
β Nice to have: FastAPI, vector databases (FAISS, Weaviate), prompt engineering
β Tools under consideration: LangChain or similar frameworks for rapid prototyping of LLM-based pipelines
Responsibilities:
β Design and build a production-grade LLM+RAG system for contextual data analysis
β Integrate external data sources and tools into the assistantβs knowledge base
β Set up and fine-tune LLMs on dedicated infrastructure or in the cloud
β Develop complex multi-step agents and orchestrated pipelines
β Build integrations with different platforms via API
β Ensure performance, scalability, and CI/CD automation of the ML systems
Requirements:
β Proven experience building real-world AI/ML products
β Deep understanding of the full machine learning lifecycle
β Experience working with popular LLM APIs and frameworks
β Ability to work independently and propose technical solutions
β Hands-on experience with LLM+RAG design patterns and prompt engineering
Required languages
English
B1 - Intermediate
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