Head of Research

About Avra Avra is a deep tech platform powered by foundational AI that translates the complexity of SMBs (Small and Medium Businesses) into strategic decisions for large enterprises. We develop our own Graph Foundation Models from the ground up—without relying on third-party solutions—to deliver innovative insights that empower some of the leading enterprises across Latin America. Today we focus on three main areas: (1) boosting underwriting (by increased recommended credit limits and reduction in delinquency); (2) increasing enterprise revenue through hyper-personalization of offerings to SMBs; and (3) customer segmentation to attract the right kind of SMBs to the sales funnel. Founded in 2024 by Viviane Meister and Bruno Alano (ex-OpenAI) and accelerated by NVIDIA, AWS and Google. The role This is a leadership role for a hands-on "player-coach" who will own and elevate our research function. Your mission is to scale the scientific vision for our Graph Foundation Models, raise the technical bar for the entire team, and bridge the gap between cutting-edge research and production-grade capabilities that move our clients\' most important metrics. You will partner deeply with Data Platform (graph & data pipelines) and Product Engineering (serving & MLOps) to transform ambitious ideas into the core of Avra\'s platform. What You\'ll Do Leadership & Scientific Strategy Own the research roadmap for our Graph Foundation Models, focusing on knowledge graphs, representation learning, self-supervised and unsupervised methods. Lead, mentor, and grow a world-class team of research scientists and engineers. Establish and champion a rigorous research cadence: from hypothesis definition and RFCs to disciplined experimentation and clear, data-driven decision-making. Hands-On Research & Engineering Design and implement state-of-the-art GNNs for our unique, large-scale graph. Solve complex problems in node, edge, and graph-level tasks, multi-scale embeddings, and temporal/inductive generalization. Build reliable, reproducible training and evaluation pipelines using PyTorch, PyG, and distributed training frameworks. Define and maintain our gold-standard benchmarks, ensuring statistically sound model comparisons. Production & Delivery Collaborate with Product Engineering to productionize models to serve both batch and online inference to our customers. Partner with our GTM teams to define success criteria for enterprise client "bake-offs" and to communicate the impact of your team\'s work to technical and executive stakeholders. Ensure our research accounts for the challenges of real-world systems, including concept drift, and improve our strategy for model deployment in regulated contexts. You Should Have 7+ years of experience in AI/ML (or a PhD + 4 years) with significant contributions in the field. A demonstrated ability to ship research into production : you have taken ideas from a paper or prototype to scalable, reliable code that delivered measurable business impact. Hands-on excellence in Python and PyTorch, with deep proficiency in graph learning libraries like PyTorch Geometric or DGL. Solid software engineering fundamentals, including testing, profiling, and building maintainable systems. Proven experience mentoring and leading technical projects or managing a small team (2-6) of scientists/engineers. Professional proficiency in both Portuguese and English . Preferred Qualifications Experience with distributed training and inference. Experience working with graph-based models. Deep knowledge of self-supervised or contrastive learning techniques, particularly for graphs. A strong publication record in top-tier AI conferences (NeurIPS, ICML, ICLR, etc.) or significant open-source contributions. #J-18808-Ljbffr