Head of Research, AI

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Take charge of the research roadmap for Foundation Models concentrating on knowledge graphs, representation learning, and both self-supervised and unsupervised methodologies.

• Guide, mentor, and develop a team of research scientists and engineers.

• Create a structured research cadence that encompasses hypothesis formulation, RFCs, experimentation, and data-driven decision-making.

• Design and deploy cutting-edge graph neural networks addressing large-scale graph challenges.

• Tackle node-, edge-, and graph-level tasks, as well as multi-scale embeddings and temporal/inductive generalization.

• Construct dependable and reproducible training and evaluation pipelines utilizing PyTorch, PyG, and distributed training frameworks.

• Set and uphold gold-standard benchmarks for statistically valid model comparisons.

• Collaborate with Product Engineering to transition models into production for both batch and online inference.

• Work alongside GTM teams to establish enterprise-client success metrics and convey business impact to both technical and executive stakeholders.

• Address concept drift and enhance model-deployment strategies within regulated environments.

⛳️ Requirements

• Over 7 years of experience in AI/ML (or a PhD plus 4 years).

• Proven ability to bring research into production, transforming concepts from academic papers or prototypes into scalable and reliable code that delivers measurable business outcomes.

• Exceptional hands-on skills in Python and PyTorch.

• In-depth expertise in graph learning libraries such as PyTorch Geometric or DGL.

• Strong foundation in software engineering principles, including testing, profiling, and developing maintainable systems.

• Demonstrated experience in mentoring and leading technical initiatives or managing a small team of 2–6 scientists/engineers.

• Professional proficiency in both Portuguese and English.

• Preferred: experience with distributed training and inference.

• Preferred: experience with graph-based models.

• Preferred: extensive knowledge of self-supervised or contrastive learning techniques, particularly in relation to graphs.

• Preferred: a strong publication record in leading AI conferences or notable contributions to open-source projects.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours with remote work options.

• Opportunities for professional development and continuous learning.

• Collaborative and innovative work environment.