Data Science Lead
Madiff
This is a senior-level remote role, but it's worth your attention if you've shipped ML projects and want to own the full stack. You'll lead the AI and machine learning architecture for a production compliance platform in regulated pharma—the kind of work that touches real compliance workflows, not toy projects.
Your day-to-day: design and optimize LLM-driven systems (RAG pipelines), set up evaluation frameworks and benchmarking strategies, implement explainability mechanisms that satisfy regulatory requirements, and collaborate with ML Engineers and Backend teams to ship AI components. You'll make decisions on embeddings, vector databases, and retrieval strategies while keeping everything reproducible and testable.
This fits you if you have hands-on depth in machine learning systems, understand how to productionize AI, and can think architecturally about scaling. A portfolio with retrieval systems, LLM work, or deployed ML models helps. Computer Science, Math, Physics, or Engineering backgrounds are common, but what matters is demonstrated capability.
Apply directly through CareerJumpShip to join Madiff. This is remote and based in the United States.
About this role
This is a remote position. We are looking for a Data Science Lead to join a high-impact AI programme operating within a strictly regulated pharmaceutical environment. The role focuses on leading the machine learning and GenAI architecture behind a production-grade compliance platform that automates regulatory validation of marketing materials. This is a strategic, enterprise-scale initiative requiring strong ownership, architectural thinking, and hands-on depth in LLM-driven systems. Responsibilities Design and evolve AI and ML architecture supporting compliance validation workflows Design and optimise LLM-driven retrieval and validation pipelines (RAG-based systems) Own evaluation frameworks, benchmarking strategies, and continuous improvement loops Implement explainability and traceability mechanisms aligned with regulatory standards Collaborate closely with ML Engineers and Backend teams on productionisation of AI components Drive decisions around embeddings, vector databases, and retrieval strategies Ensure reproducible, testable, and high-quality AI workflows Support scaling the platform into an enterprise-grade AI solution Lead technical discussions across product, engineering, and compliance stakeholders Requirements Strong hands-on background in Data Science and applied Machine Learning Proven experience designing and deploying LLM-based systems in production Practical experience with Retrieval Augmented Generation architectures Experience with vector databases and embedding pipelines Strong Python expertise and familiarity with modern AI frameworks Experience designing model evaluation and validation frameworks Ability to operate in regulated or compliance-heavy environments Strong ownership mindset and ability to influence architectural decisions Confident communication skills in cross-functional environments Nice to have Experience in pharmaceutical, healthcare, or other regulated industries Exposure to explainable AI methodologies or frameworks Experience with document intelligence and NLP-heavy pipelines Background in enterprise-scale AI platforms rather than proof-of-concept environments Benefits Solid, competitive salary Work in a multinational environment on international projects Comprehensive healthcare Long-term B2B contract with a stable project pipeline Fully remote working model Originally posted on Himalayas
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