Research Manager - Foundation & World Models

About the role

Datadog is hiring a Research Manager within its AI Research team (DAIR) in Paris. You will lead a team working on fundamental research in foundation models and world models while staying deeply involved in the technical direction. The role suits a researcher or technical leader who wants to keep a strong hands-on research identity while building and leading a high-performing team.

Key responsibilities

• Lead research in foundation models, world models and multimodal learning, setting the technical direction of research programs grounded in observability and security
• Guide and mentor researchers and research engineers, taking part in research strategy, experimentation, model development and technical problem-solving
• Train large-scale multimodal models on telemetry data such as metrics, logs, traces, topology and events
• Advance pre-training, representation learning, world modeling, scaling and evaluation for models that learn the dynamics of complex distributed systems
• Work with Research, Product and Engineering teams to turn research advances into scalable Datadog capabilities
• Contribute to research publications, present at top-tier conferences such as NeurIPS, ICLR and ICML, and help open-source key model artifacts and benchmarks

Required profile

• PhD in Computer Science, Machine Learning or a related field, or equivalent experience
• Proven ability to lead technically ambitious research at meaningful scale, in an industry lab, startup, university or similar setting
• Track record of research impact through publications, model or system contributions, or widely used research artifacts
• Experience leading and mentoring teams of researchers or engineers while staying hands-on in technical direction
• Ability to explain complex research findings to both technical and non-technical audiences

Required skills

• Deep expertise in foundation models, world models, multimodal learning or generative modeling
• Hands-on experience designing, training or evaluating large-scale deep learning models (e.g. large language models); experience with multimodal or non-text data is a strong plus

What we offer

• Performance-based earnings and new-hire stock equity (RSUs) and an employee stock purchase plan
• Professional development, product training and career pathing
• Sales training in MEDDIC and Command of the Message
• Intradepartmental mentor and buddy program, and access to employee resource groups
• Global benefits for employees and dependents aged 6+, giving programs and an inclusive culture