We are seeking a talented and motivated Senior Data Scientist to join our AI team. In this role, you will lead the development of our best-in-class conversational heart health agent. You will work on highly complicated challenges, spanning from deep research to full-scale production. Your work will leverage cutting-edge Generative AI and agentic architectures to help solving one of the world's most significant and urging clinical issues: cardiovascular disease. Your contribution will directly impact healthcare practices and enhance the well-being of individuals globally.
Responsibilities
You will take ownership of designing and building a conversational heart health agent, utilizing advanced LLM techniques, RAG (Retrieval-Augmented Generation), and flow engineering.
You will architect and implement complex agentic and multi-agentic graphs using tools like LangChain and LangGraph to handle intricate clinical logic and user interactions.
You will not just research; you will write production-grade code. You will be responsible for optimizing, deploying, and maintaining these systems in a live environment.
You will implement robust monitoring and debugging workflows for agentic products (using tools like LangFuse or LangSmith) to ensure safety, accuracy, and performance.
You will work closely with product managers and clinical experts to translate clinical research into digital insights and conversational flows that will be used on a daily basis.
You will innovate and make new ideas happen fast, in an agile way, keeping up with the rapidly evolving landscape of GenAI.
Responsibilities
You will take ownership of designing and building a conversational heart health agent, utilizing advanced LLM techniques, RAG (Retrieval-Augmented Generation), and flow engineering.
You will architect and implement complex agentic and multi-agentic graphs using tools like LangChain and LangGraph to handle intricate clinical logic and user interactions.
You will not just research; you will write production-grade code. You will be responsible for optimizing, deploying, and maintaining these systems in a live environment.
You will implement robust monitoring and debugging workflows for agentic products (using tools like LangFuse or LangSmith) to ensure safety, accuracy, and performance.
You will work closely with product managers and clinical experts to translate clinical research into digital insights and conversational flows that will be used on a daily basis.
You will innovate and make new ideas happen fast, in an agile way, keeping up with the rapidly evolving landscape of GenAI.
Requirements:
5+ years of hands-on experience in developing machine learning and statistical models using Python (Required).
MSc in Computer Science, Electrical Engineering, Statistics, Applied Math or other related fields (Required).
Deep experience with Generative AI, specifically LLMs, Prompt Engineering, RAG, and flow engineering (Required).
Proven experience building agentic and multi-agentic graphs using LangChain or LangGraph (Required).
Experience with monitoring and debugging agentic products in production using tools such as LangFuse or LangSmith (Required).
Strong production experience with the proven ability to transfer research ideas into a scalable, production-grade system.
Experience working with PyTorch / TensorFlow and other standard DL tools (Required).
Expertise in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, genetic algorithms, and anomaly detection.
Comfortable working in a dynamic group with several ongoing concurrent projects, both in the research phase and production phase.
Advantages:
PhD in Computer Science, Electrical Engineering, Statistics, Applied Math or other related fields.
Experience in the healthcare industry and working with clinical data / EMR.
5+ years of hands-on experience in developing machine learning and statistical models using Python (Required).
MSc in Computer Science, Electrical Engineering, Statistics, Applied Math or other related fields (Required).
Deep experience with Generative AI, specifically LLMs, Prompt Engineering, RAG, and flow engineering (Required).
Proven experience building agentic and multi-agentic graphs using LangChain or LangGraph (Required).
Experience with monitoring and debugging agentic products in production using tools such as LangFuse or LangSmith (Required).
Strong production experience with the proven ability to transfer research ideas into a scalable, production-grade system.
Experience working with PyTorch / TensorFlow and other standard DL tools (Required).
Expertise in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, genetic algorithms, and anomaly detection.
Comfortable working in a dynamic group with several ongoing concurrent projects, both in the research phase and production phase.
Advantages:
PhD in Computer Science, Electrical Engineering, Statistics, Applied Math or other related fields.
Experience in the healthcare industry and working with clinical data / EMR.
This position is open to all candidates.
