Research Scientist, AI Verification

Meta; Paris; Hybride; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Meta is seeking Research Scientists to join our AI Verification team. You will work on model training, evaluation benchmarks, and trustworthy AI, bridging symbolic verification with neural AI.

Qualifications include a PhD in CS/AI/ML, publications at top AI conferences, experience with large-scale training infra and data pipelines, and ability to design robust evaluation benchmarks. You will need work authorization in France.

Qualifications

• PhD in Computer Science, AI, ML, or related field.
• Experience in ML model evaluation, training pipelines, or benchmark and agent design and evaluation.
• Publications in ML/AI or related fields.
• Author publications at peer-reviewed AI conferences (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP).
• Experience with large-scale training infrastructure and data pipelines.
• Experience designing evaluation benchmarks for large AI models or agents.
• Familiarity with formal verification or automatic program analysis.

Responsabilités

• Join the AI Verification team to advance trustworthy AI models.
• Design and evaluate data and environments to train ML models and benchmarks.
• Develop evaluation benchmarks for agents and models.
• Connect symbolic verification with neural AI.

Connaissances

ML model evaluation

Publications in ML/AI

Large-scale training infra

Evaluation benchmarks design

Formal verification / program analysis

Formation

PhD in Computer Science / AI / ML

Description du poste

Meta is looking for Research Scientists to join our AI Verification team.

For these positions we are looking for people with experience in model training or agentic AI to complement the verification expertise in our team. The candidate will have experience in building trustworthy and reliable AI models and agents, including designing comprehensive evaluation benchmarks, optimizing training processes, and ensuring high-quality data pipelines. The candidate will help to create and evaluate data and environments to train ML models, and benchmarks to judge agents and models. The overall focus of the team is on using formal program verification to make AI better (safer, more reliable), and on using AI to make formal verification better (more feasible); these ML roles will be pivotal in connecting symbolic verification to neural AI.

• Currently has or is in the process of obtaining a PhD in the field of Computer Science, Artificial Intelligence, Machine Learning, or a related field
• Experience in ML model evaluation, training pipelines, or benchmark and agent design and evaluation
• Publications in areas of Machine Learning, AI, or related fields
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization throughout employment
• First-author publications at peer-reviewed AI conferences (e.g. NeurIPS, ICML, ICLR, *ACL, EMNLP)
• Experience with large-scale training infrastructure and data pipelines
• Experience designing and implementing evaluation benchmarks for large AI models or agents
• Experience with formal verification or automatic program analysis