Python Developer AI/ML

Opis pracy

About the job

Location: Gliwice, Hybrid

Stawka: 25.000 PLN brutto, + 75% PKUP - uop

About Us

Join our dynamic co.brick Observe team, where you'll have the opportunity to co-create and shape the development direction of the innovative AI-driven platform. Our mission is to create a seamless, AI-powered ecosystem that monitors systems in real-time, prevents failures, reduces downtime, and delivers fully autonomous 24/7/365 support.

You will drive Proof of Concepts (PoCs) and MVPs from the ground up in a highly collaborative, fast-paced environment. The work you do here will define the next generation of AI-powered user interactions. We're looking for someone with a deep passion for innovation who excels in the agile, high-energy atmosphere of a startup. If you're ready to build what's next, let's talk.

Key Responsibilities

• Design and implement scalable backend services in Python that support, ML and generative AI solutions, for knowledge inference and user support.
• Develop and maintain semantic knowledge bases using Retrieval-Augmented Generation (RAG) processes to enhance the system's ability to provide accurate, contextually relevant information and support.
• Continuously improve data inference models to enable better predictions, and automated recommendations, contributing to the strategic development of the system's functionalities.
• Collaborate with cross-functional teams to ensure the seamless integration of generative AI and semantic knowledge solutions into the broader system, improving overall performance and user experience.
• Development of AI/ML Proof of Concepts (PoCs) and Minimum Viable Products (MVPs), showcasing innovative solutions and demonstrating the potential of new technologies in real-world applications.
• Collaborating with other team members on best practices, code quality, and new AI technologies.
• Stay informed about emerging AI technologies, trends, and best practices. Apply this knowledge to improve data engineering processes and techniques continuously.
  
  

• 3+ years of Python development experience, with proven experience in driving projects from concept to deployment.
• Strong hands-on experience in generative AI/NLP solutions and Machine Learning model development and deployment.
• Ability to argue for technical decisions and influence the product's development direction.
• Familiarity with semantic knowledge bases and Retrieval-Augmented Generation (RAG) processes, along with experience in integrating AI solutions for knowledge inference and support systems.
• Experience working in cross-functional teams, collaborating with data scientists and engineers to ensure smooth integration of AI solutions into complex systems.
• Strong knowledge of conversational, LLM-based AI agents, and multiagent systems.
• Excellent communication skills, allowing for the clear presentation of complex technical concepts to both technical and non-technical audiences.
  
  

• Strong experience with Python frameworks (e.g. FastAPI) including designing RESTful APIs, implementing asynchronous endpoints, and building scalable applications following best practices.
• Experience with version control systems (e.g. Git).
• Knowledge of various database systems (e.g. PostgreSQL, Redis)
• Experience with setting up and managing vector data bases (e.g. Qdrant, PGVector)
• Proficiency with LLM-specific models, prompt engineering, ReAct agents (Reasoning and Acting), libraries, and frameworks, such as Hugging Face, LlamaCloud, or LLMs APIs (eg. OpenAI API),
• Experience with fine-tuning large language models for specialized tasks.
• Experience with MLOps tools relevant to generative AI, such as LangChain, LlamaIndex, prompt engineering, and scaling LLM deployments.
• Strong understanding of retrieval-augmented generation (RAG) systems
• Strong analytical and problem-solving skills
• Excellent communication and teamwork abilities to collaborate effectively with cross-functional teams.
  
  

• Experience and knowledge of AI/ML models for anomaly detection, prediction and similar tasks in observability systems with the ability to leverage these models to enhance system reliability and proactively resolve issues.
• Experience with prototyping frameworks such as Streamlit to enable rapid development and deployment of user interfaces for prototype applications and functionalities.
• Familiarity with Model Context Protocol (MCP)