Senior Software Engineer – Machine Learning, AI

Gigafactory Berlin forms the perfect basis for rolling out Tesla's incredible success story in Europe. The most important pillar for this is our employees. Their passion, motivation and engagement ensure that we consistently achieve our goals.

The Role

We are seeking talented Software Engineers - ML, AI to join our dynamic team, focusing on building Retrieval-Augmented Generation (RAG) chatbots powered by open-source Large Language Models (LLMs) and evolve into creating advanced AI agents. This role is ideal for engineers passionate about natural language processing (NLP), machine learning, and backend development. You will have the opportunity to develop cutting-edge AI solutions and contribute to the next generation of intelligent chatbot systems.

• Design, develop, and maintain RAG-based chatbots by leveraging open-source large language models (LLMs) like LLaMA, Falcon, and GPT-J, integrating them with external knowledge bases (e.g., vector databases such as Pinecone, FAISS)
• Build and optimize NLP pipelines for tasks such as text retrieval, embeddings, dialogue management, and intent recognition
• Architect scalable and robust backends using Python frameworks like FastAPI or Flask, integrating APIs, external tools, and databases to support chatbot and AI system functionality
• Collaborate with cross-functional teams, including product and design, to deliver user-friendly, intuitive solutions tailored to business and customer needs
• Experiment with and fine-tune LLMs, improve chatbot and agent performance using prompt engineering, and ensure scalable, low-latency deployments in production
• Explore, design, and implement AI agents capable of performing autonomous tasks, including reasoning, planning, decision-making, and integrating with external tools and APIs for multi-step task execution
• Continuously research and stay updated on advancements in LLMs, NLP, and AI, applying cutting-edge techniques to enhance chatbot and AI agent capabilities
• Ensure best practices for software development, including CI/CD pipelines, code quality, scalability, and proper documentation, while participating in code reviews and team improvement efforts