Careers

Sentra is on a mission to help cloud-driven organizations regain control and secure their full data lifecycle. We are a fast-growing startup based in Tel Aviv (near the train station), backed by a strong founding team and leading investors. We’re looking for a Senior AI Research Scientist to join our Classification group and help shape the future of data security through advanced machine learning and AI research.

The Classification Team sits at the core of Sentra’s product, responsible for discovering sensitive data and identifying the most critical risks across cloud environments. The team blends research and engineering - developing state-of-the-art models for entity recognition, contextual understanding, and sensitive data detection at scale.

As a Senior AI Research Scientist, you will lead research and development of advanced AI models - from LLMs and NER systems to generative and self-supervised architectures - that power Sentra’s data classification capabilities. You’ll explore emerging AI techniques, build prototypes and bring them to production.

• Research & Innovation: Design and evaluate novel AI and NLP approaches (LLMs, generative models, self-supervised methods) to enhance entity recognition and contextual understanding.
• Prototype to Production: Develop proof-of-concept models and collaborate with MLOps and engineering teams to harden and deploy them in production environments.
• Experimentation Frameworks: Build tools and pipelines for large-scale experimentation, model evaluation, and continuous improvement.
• Data-Driven Insights: Leverage Sentra’s unique datasets to define key metrics, drive iterative improvements, and balance precision-recall trade-offs.
• Cross-Functional Collaboration: Work closely with Product and Engineering to align research direction with business and customer impact.

• 7+ years of experience in machine learning or AI research, with deep expertise in NLP, LLMs, or Generative AI.
• Proven track record of delivering AI models into production, including model deployment, monitoring, and lifecycle management.
• Strong proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow).
• Hands-on experience with large-scale data processing (Spark, Ray, or similar) and cloud platforms (AWS, GCP, or Azure).
• Solid understanding of MLOps practices, including continuous training, evaluation, and model versioning.Excellent communication and collaboration skills, especially when working across product and engineering teams.

Nice to have:

• Experience in data security, privacy, or compliance domains.
• Familiarity with LLM fine-tuning, and prompt optimization.
• Experience with cloud-based AI training and fine-tuning frameworks.
• Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, or related field.