Descripción de la oferta
At M47, we spark AI! We help multinational tech companies understand how AI can drive their strategic objectives, effectively plan an implementation roadmap, and facilitate change management. By leveraging AI, businesses achieve higher productivity, more satisfied clients, and better-informed decisions. Join us in making the future more intelligent! About your day-to-day: You will join our AI Voice Assistant project to ensure seamless user interactions. Our mission is to support the training of Machine Learning and Natural Language Processing models to expand the model's responsiveness across different languages. To do so, we work in a native language environment. Scripting & Automation: Design and write Python scripts from scratch to process, clean, and validate massive text datasets (JSON, XML, CSV). Algorithmic Analysis: Investigate model failures by analyzing logs and data patterns, using code to identify root causes rather than manual review. Write complex Regex rules to automatically detect and fix linguistic errors across thousands of lines of data. Troubleshoot technical issues during data ingestion and export, working with the core engineering team to resolve encoding or formatting errors. Provide technical feedback to improve internal annotation tools and automate repetitive tasks using shell scripts or simple bots. Version Control: Manage datasets and codebase changes using Git (branching, committing, and merging). This is for you if you have: BS/MS in Computer Science, Software Engineering, Computational Linguistics, or a related field. Native level of Danish (Spoken and Written) Strong proficiency in Python . You must be able to proceed with coding tasks independently without heavy reliance on LLM tools. Comfortable working in a Unix-based environment (Bash, grep, piping commands). Problem-solving mindset: You prefer to write a script to fix a problem once, rather than fixing it manually 100 times. Strong English communication skills. Bonus points if you have: Practical experience with NLP libraries such as spaCy, NLTK, or Hugging Face. Experience with SQL for querying datasets. Familiarity with cloud environments (AWS, Azure). Previous experience in Software QA or Test Automation. What is in it for you?
