Senior/Mid/ - AI Research Engineer - Agents Team - MAD/BCN

About the role

Are you ready to take part in the upcoming AI revolution of the business world? If the answer is a resounding "yes," we have an extraordinary opportunity for you! About Us Aily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models and agentic AI to give business leaders clear, actionable insights in real time. Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations powered by GenAI that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day. Founded in 2020 in Munich, Aily Labs has grown into a global team of 300+ people across Munich, Barcelona, Madrid, Cluj, and New York. Our mission is to democratize AI in business and enable leaders to Lead Boldly , turning complex data into decisions that drive real, measurable impact. About the Team & The Role: We are looking for exceptionally smart and driven AI Research Engineers to join a small, highly technical, and specialized research team at Aily. This team operates at the bleeding edge of AI, focusing on high-impact, moderately higher-risk projects that directly influence our end product. While your day-to-day work will heavily involve Language Models and Agentic AI, we expect you to be deeply versed in all of Machine Learning. You will have the runway to dive deep into model architectures, debug complex algorithmic behaviors, fine-tune state-of-the-art models, and translate your findings into deployable product enhancements. While our ultimate goal is delivering business value, we maintain a strong culture of scientific rigor. If an experiment yields novel, high-quality results, you will have the opportunity and support to publish your findings in top-tier AI conferences (e.g., NeurIPS, ICLR, ACL). Core responsibilities (by seniority) Core responsibilities (by seni ority) Mid AI Research Engineer (2-3+ years of experience) Experiment & Build: Design, set up, and execute experiments focusing on LLMs, Agentic AI, model fine-tuning, and broader ML systems. Manage reproducible research pipelines, version code, and data, and select the right frameworks for prototyping. Algorithmic Debugging: Actively investigate why a model isn't converging, why outputs are inconsistent, or why results are unreliable across different ML architectures. Code Quality: Write clean, modular code (effective use of classes, functions, and documentation) following strict software engineering best practices. Autonomous Delivery: Deliver projects with a high degree of autonomy. Present results clearly, explain the AI behind your findings, and align experiments with team priorities. Senior AI Research Engineer (4+ years of experience) All of the above, plus: End-to-End Ownership & Strategy: Deliver clean, extendable research pipelines end-to-end. Set and drive the overall research strategy based on expected business leverage, identifying domain-wide opportunities. Bridge Research & Product: Translate experimental findings and research breakthroughs into clear, actionable, and deployable directions for the Data Science, MLE, and Product teams. Mentorship & Leadership: Supervise and mentor team members, delegate tasks effectively, and drive the adoption of impactful research innovations across broader engineering teams. Advanced Systems & MLOps: Utilize advanced knowledge of MLOps to define and develop robust E2E code pipelines for cutting-edge models. External Presence: Act as a representative of Aily's research efforts, build university relationships, and spearhead efforts to publish papers at top conferences. Who We're Looking For The Academic Background: A Master's degree (required) in a highly technical and quantitative field such as Mathematics, Physics, Engineering, Computer Science, or a rigorous double degree. The Foundations (All of ML): You have zero gaps in your machine learning fundamentals. While you will work extensively with LLMs, you have a deep, mathematical intuition for classical ML, deep learning, and how models learn (and fail) across the board. The Tech Stack & Tools: You have extensive, highly proficient experience with Python and SQL. You possess a strong track record working with Language Models, Agentic AI workflows, and deep expertise in model fine-tuning (experience with Knowledge Graphs is a plus). MLOps: You are not just a researcher; you are highly capable of deploying solutions into production environments using tools like Docker and other containerization technologies. The Mindset (Autonomous & Sharp): You are exceptionally smart, highly autonomous, and thrive in ambiguity. You don't just wait for instructions; you proactively identify problems and rigorously test solution