AI Engineer (Madrid) Madrid
Role details
Job location
Tech stack
Job description
future of Duckbill's user-facing experience. * Leverage the latest innovations in AI and ML to provide a hyper-personalized experience to our users, including the development of high-engagement recommendation systems. * Build tools to maximize the output and quality of our human personal assistants (copilots), reimagining the collaboration between humans and machines in the virtual assistant space. * Automate task execution by leveraging the entire AI stack, from traditional ML to the latest LLM-agent frameworks. * Improve human task execution quality by enhancing our intelligent information retrieval systems, utilizing search and RAG techniques. * Contribute to our operations team's excellence by building smart monitoring and intervention systems. * Enhance our AI ops stack by designing and improving our evaluation frameworks, allowing the team to iterate on prompts, models, and approaches with both agility and thoroughness. * Enhance our human annotation flow stack to
Requirements
enable leveraging our human resources for annotation, model comparison, and golden dataset generation. * Maximize the value extracted from our proprietary data using state-of-the-art techniques (fine-tuning, RLHF, RAG, etc.), critically contributing to the defensibility of our AI strategy. What we look for * 4+ years of experience in an ML engineering role. * Proficiency in machine learning, with experience in areas such as Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Modeling. Specialized knowledge in recommender systems is a plus. * Strong engineering skills in Python and data manipulation skills in SQL. * Solid knowledge of the main patterns in ML model deployment, both online (API-based) and offline (batch jobs), with the ability to design production-grade solutions. * Experience with the entire MLOps stack, especially in experiment/model performance tracking and model monitoring in production. * Strong product and business intuition, with a deep understanding of what makes an ML project a business success. * Knowledge of the foundations of the LLM stack, including main foundational models (both closed and open-source), prompt engineering techniques, evaluation frameworks, and function calling. Nice to have * Strong understanding of embeddings and RAG systems. * Basic knowledge of LLM agent architectures and the main stack libraries (e.g., langchain, llama_index). * Prior experience with any of the components of our backend stack, such as Django, Celery, MongoDB, and PostgreSQL. What we offer * Competitive base salary plus stock option package. * International, positive, dynamic, and motivated work environment. * 10% of the time dedicated to off-backlog research on applying SOTA to Duckbill's challenges. * Hybrid work model (highly flexible, with a preference for two in-person days per week). * Health insurance. #J-18808-Ljbffr
