Lead AI Engineer, Biomedical & Vigilance Innovation

California, US residents  () .

** The job details are as follows:*
* Who We Are

We are the first publicly-traded biotech or pharmaceutical company to take the form of a public benefit corporation. Our public benefit purpose is to provide a brighter future for patients through the development of novel pharmaceutical therapies; and technologies that expand the availability of transplantable organs.

United Therapeutics (Nasdaq: UTHR) seeks to travel down the corridors of indifference to develop treatments for rare, deadly diseases. We were founded in 1996 by a family seeking a cure for their daughter's pulmonary arterial hypertension (PAH). Today, we have six FDA-approved therapies that treat PAH, pulmonary hypertension associated with interstitial lung disease (PH-ILD) and neuroblastoma, a rare pediatric cancer. Our near-term pipeline seeks to develop additional therapies for PAH and pulmonary fibrosis (PF).

The cure for end-stage life-threatening diseases like PAH, PH-ILD, PF, and many others is an organ transplant, but only a small percentage of donated organs are available to address the vast need. For this reason, we are working to create manufactured organs to address the shortage of kidneys, hearts, lungs, and livers available for transplant. We believe an unlimited supply of tolerable, transplantable organs will eliminate the transplant waiting list and cure end-stage organ diseases for which transplant is not currently an option.

Who You Are

We are seeking a Lead AI Engineer, Biomedical & Vigilance Innovation with a start-up mindset to drive the design, development, and deployment of advanced AI solutions that transform how biomedical insights are generated and how safety signals are detected, assessed, and acted upon, as well as deploying artificial intelligence solutions that strengthen biomedical research, patient safety, and next-generation vigilance capabilities.

This role operates at the intersection of data science, software engineering, and medical safety, applying advanced analytics, machine learning, and automation signal detection, case intelligence, business efficiency, and evidence generation from various sources of scientific and RWD. The position will partner closely with safety physicians, clinical scientists, epidemiologists, regulatory leaders, and technology teams to create scalable platforms that support proactive risk management and accelerate informed decision-making across the product lifecycle.

This role is instrumental in shaping the future state of digital vigilance and precision medicine.

+ Design, build, validate, and maintain machine learning, natural language processing, and generative AI solutions for biomedical and pharmacovigilance use cases

+ Develop tools that support adverse event intake, case triage, coding assistance, duplicate detection, signal prioritization, and trend analysis

+ Engineer predictive models to identify emerging risks, patient patterns, and operational bottlenecks

+ Translate complex scientific and business requirements into production-ready AI applications

+ Deep understanding & Hands-on experience of know-how of model definitions and fine-tuning models to make them efficient and fit for purpose to UT PV business use cases

+ Define and execute a bold technology strategy spanning the Global Patient Safety covering usage of AI in day-to-day PV operations, analytical sciences, signal detection, process scale up with a clear mandate to embed AI, machine learning, and agentic automation throughout, within the UT Global Patient Safety Organization

+ Drive the architecture, development, and delivery of next-generation platforms for pharmacovigilance technological AI initiatives

+ Integrate structured and unstructured datasets from safety databases, clinical systems, literature sources, real-world evidence, and external repositories

+ Hand-on experience of creating staging schemas and data mining varied sources to uncover hidden trends & patterns turning into meaningful insights

+ Build scalable pipelines for ingestion, transformation, and quality control of biomedical data

+ Apply ontology mapping, terminology harmonization, and metadata strategies across MedDRA, WHO Drug, and related standards

+ Ensure robust data lineage, traceability, and audit readiness

+ Support modernization of pharmacovigilance and Organovigilance systems through AI enabled automation and decision support tools

+ Improve case processing efficiency, medical review, and governance reporting through AI-enabled solutions

+ Contribute to next-generation surveillance models for novel modalities including xenotransplantation, cell therapy, gene therapy, and organ-based therapeutics

+ Develop AI enabled dashboards and visualization tools that enable rapid interpretation of safety trends

+ Ensure AI models and digital tools are developed in alignment with GxP, privacy, security, validation, and regulatory expectations

+ Support model governance frameworks including performance monitoring, unbiased detection,…