Data & ML Engineer (LLM & NLP Focus)

Responsibilities:

• Design, develop, and maintain robust, serverless data pipelines (ELT) for collecting, processing, and transforming diverse text and image data, ensuring high data quality and accessibility for our LLM-powered AI services.
• Design, develop, and maintain AI Services built around Large Language Models, alongside traditional text and image analysis, and generative AI capabilities.
• Integrate AI Services into our AI Service Factory for rapid prototyping and seamless integration with MIGO.
• Develop, fine-tune, and optimize Large Language Models for tasks such as text classification, sentiment analysis, text generation, summarization, and retrieval-augmented generation (RAG).
• Prepare and preprocess data for LLM and machine learning tasks, including feature extraction, normalization, and handling imbalanced datasets, specifically optimized for ELT workflows.
• Evaluate model performance using appropriate metrics and continuously refine models to improve accuracy and efficiency.
• Conduct research and experimentation to explore new LLM techniques and stay up-to-date with industry trends.

Qualifications:

• Strong foundation in Large Language Models (LLMs), deep learning architectures, and their applications.
• Proficiency in Python and popular machine learning/deep learning libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn).
• Solid experience with ELT (Extract, Load, Transform) data processing and pipeline orchestration, preferably in a serverless cloud environment.
• Extensive experience with natural language processing (NLP) tasks, particularly those leveraging LLMs for text classification, sentiment analysis, text generation, and understanding.
• Understanding of computer vision techniques for image analysis and object recognition (where relevant for multimodal applications).
• Knowledge of data preprocessing, feature engineering, and model evaluation techniques, especially for LLMs.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills.
• Extensive experience with Google Cloud Platform (GCP), specifically with serverless data services (e.g., Dataflow, BigQuery, Cloud Functions, Pub/Sub) and LLM/machine learning services (e.g., Vertex AI, Cloud AI Platform, LLM APIs).
• German language proficiency at a minimum B2 level.

Preferred Qualifications:

• Familiarity with MLOps and LLMOps practices for managing models in production environments.
• Experience with research and publication in relevant fields (LLMs, NLP).
• Experience with real-time data processing and streaming technologies in a serverless context.

Benefits:

• Learning Opportunities: Cutting-edge projects, mentorship, career advancement.
• Competitive Compensation: Competitive salary, benefits, virtual stock options.
• Agile Culture: Collaborative young team in a fun working environment.
• Impactful Work: Innovative solutions, purpose-driven company.