Summary: This position involves developing and deploying advanced AI solutions to enhance clinical workflows, fostering technical excellence and collaboration within the engineering team.

Responsibilities:

* Design, build, and deploy scalable AI solutions, including Agentic AI and LLM multimodal chatbots.

* Mentor engineers and data teams to promote technical excellence and innovation.

* Architect and manage AI/ML infrastructure using Azure or On-Prem Openshift with Kubernetes.

* Optimize model deployments for low-latency and high-throughput applications.

* Establish frameworks for model evaluation, validation, and monitoring ensuring fairness and transparency.

* Drive a modern AI development lifecycle utilizing coding assistants and uphold a strict PR-based workflow.

* Implement Knowledge Graphs and LLMs for biomedical data modeling.

* Develop Reinforcement Learning models for Clinical Decision Support Systems.

* Collaborate with cross-functional teams to ensure AI solutions integrate into clinical workflows using FHIR/HL7 standards.

Must Haves:

* Bachelor's or Master's in Computer Science, Data Science, Statistics, or a related field.

* 6+ years in AI, machine learning, or data science with a track record of impactful solutions.

* Experience deploying machine learning models in production using Kubernetes.

* Knowledge of optimizing GPU inferencing and performance tuning specific to frameworks.

* Proficiency in model evaluation techniques and AI explainability methods.

* Experience with AI-assisted development tools like Cursor and GitHub Copilot.

* Familiarity with automated testing frameworks and CI/CD practices.

* Expertise with Knowledge Graphs and graph databases such as TigerGraph or Neo4j.

* Familiarity with Reinforcement Learning concepts.

* Proficiency in Python and ML/Data Science libraries.

* Strong experience with cloud platforms (AWS, Azure, GCP).