Principal AI/ML Architect

Role overview A senior machine learning architect role focused on leading ambitious client engagements around agentic AI, conversational copilots, and large-scale search and recommender systems. The position blends hands-on technical leadership with strategic client advisory work, suited to a practitioner who has shipped production AI systems and can engage credibly at executive level.

Responsibilities - Partner with client stakeholders to scope business problems and translate them into scalable ML and agentic AI architectures. - Serve as the primary technical point of contact, explaining complex concepts to executive audiences and engineering teams. - Lead, mentor, and provide technical direction to ML engineering teams while owning overall project delivery. - Design and build agentic workflows, multi-agent systems, and retrieval-augmented generation pipelines that go beyond conventional ML. - Steer projects end-to-end, from discovery and architecture through deployment, monitoring, and iteration in production. - Drive innovation in agent-based modeling, complex RAG patterns, and high-stakes decision-support systems.

Requirements - 8+ years of professional experience in machine learning and software engineering, with a record of architecting and delivering large-scale production AI/ML systems. - Significant client-facing experience in consulting or architectural roles, comfortable leading technical discussions with senior stakeholders. - Proven leadership and project management experience guiding engineering teams on complex software initiatives. - Deep expertise in Python and the data science ecosystem (Pandas, NumPy, Scikit-learn). - Expert-level knowledge of large language models, agentic design patterns, RAG, fine-tuning, and classical ML at scale, including recommender algorithms and learning to rank. - Strong architectural foundation in software engineering, MLOps, and cloud infrastructure (AWS or GCP), with a BSc, MSc, PhD in Computer Science, Engineering, or a related field, or equivalent practical experience.

Nice to have - Hands-on experience with frameworks and tools such as LangChain, LangGraph, LlamaIndex, Langfuse, MLflow, and Kubeflow. - Familiarity with TensorFlow, LightGBM, CatBoost, FastAPI, and Docker. - Background in low-latency search, ad-tech, or recommender platforms serving high traffic.

Benefits and work setup - Fully remote position based in Spain. - Senior leadership influence over technical direction and the studio's engineering culture. - Competitive compensation with a clear path for professional and personal development.