Data Science Lead

📋 Description

• Lead architecture and evolution of ML and GenAI capabilities for automated regulatory validation
• Design and optimize LLM-powered retrieval and validation pipelines (RAG architectures).
• Establish evaluation frameworks, benchmarking, and continuous improvement for AI performance.
• Develop explainability, traceability, and validation mechanisms for regulatory compliance.
• Collaborate with ML Engineers and Backend Engineers to productionize AI components in enterprise
• Drive decisions around embeddings, vector databases, and related AI infrastructure.

🎯 Requirements

• Strong hands-on experience in Data Science, ML, and production AI systems.
• Proven experience designing and deploying LLM-based solutions in production.
• Practical experience with Retrieval Augmented Generation and LLM-driven retrieval workflows.
• Experience with vector databases, embeddings, and embedding-generation pipelines.
• Strong Python programming skills and familiarity with modern ML/AI frameworks.
• Demonstrated experience designing model evaluation, benchmarking, and validation frameworks.

🎁 Benefits

• Competitive salary package.
• Opportunity to work on international, high-impact AI initiatives within a regulated enterprise
• Comprehensive healthcare coverage.
• Long-term B2B contract with a stable project pipeline.
• Fully remote working model.
• Opportunity to work with modern LLM, RAG, ML, and AI platform technologies.