Senior Healthcare Data Scientist (AI/ML)

Quick Facts

• Role: Senior Healthcare Data Scientist (AI/ML)

• Focus: Building and deploying AI agents, GenAI models, and ML solutions

• Platform emphasis: Microsoft Azure (Azure Data & AI services)

Description

You will design, build, and deploy secure, scalable AI agents and machine learning models for healthcare use cases. The work includes experimenting with GenAI and agentic workflows powered by LLMs, evaluating performance, and continuously improving conversation, decision-making, adaptability, and safety via guardrails. Solutions will be integrated into applications and workflows for robust cross-platform deployment and an improved user experience.

Responsibilities

• Develop and deploy AI agents and machine learning models using ML frameworks

• Design agentic systems leveraging LLMs, planning algorithms, and decision-making frameworks

• Build secure, scalable agents and integrate them into application workflows

• Experiment with GenAI models and agentic workflows

• Advance agent capabilities through research, performance evaluation, safety mechanisms, and guardrails

• Optimize performance using feedback mechanisms, reinforcement learning, and user interaction analysis

• Collaborate across the stack (backend services, model pipelines, frontend interfaces)

• Prototype rapidly and iterate in a startup-style environment; support incubation efforts

• Work with senior engineers and researchers to deliver production-grade AI systems

Requirements

• Deep expertise in AI/ML

• Proficiency in Python (and other relevant programming languages)

• Experience building and deploying AI agents and machine learning models

• Strong expertise in Microsoft Azure, including Azure Data and AI platforms such as Databricks, Fabric, and Microsoft AI Foundry

• Experience building and experimenting with GenAI models and agentic workflows

• Ability to design intelligent AI agents using LLMs, planning algorithms, and decision-making frameworks

• Experience with safety and guardrail mechanisms for AI agents

• Experience improving agent performance via research, performance evaluation, feedback loops, reinforcement learning, and user interaction analysis

• Ability to collaborate across backend services, model pipelines, and frontend interfaces

Benefits

• Opportunity to prototype rapidly and contribute to incubation-style efforts

• Collaboration with senior engineers and researchers to deliver production-grade AI systems

• Work on security-focused intelligent AI agent development