Senior AI/ML Engineer

Company: Pedestal Health

Location: Boston, MA (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-10-03

About this role

About Pedestal Health
Pedestal Health (formerly Target RWE) combines deep health system partnerships, longitudinal data curation at scale, and modern study design to build continuous, high-quality evidence for life sciences organizations. The company partners with pharmaceutical and biotech companies, providers and payers to generate rigorous, multimodal evidence that supports clinical, regulatory and strategic decision-making across the full lifecycle of care. Pedestal Health is committed to advancing medical decision making to improve outcomes for patients. Pedestal Health is a Highlander Health company. Learn more at pedestalhealth.com.


The Role
Pedestal Health is seeking a Senior AI/ML Engineer to join our Technology team and help shape the next generation of real-world evidence solutions. In this hands-on role, you will design, develop, and deploy scalable machine learning systems — with a particular focus on large language model (LLM) applications. These systems enable our researchers, statisticians, and clinical teams to extract deeper insights from complex healthcare data. Your work will directly support Pedestal Health’s mission of advancing clinical research and informing better healthcare decisions at scale.


This is a highly collaborative position. You will partner closely with software engineers, data scientists, research scientists, and product managers to build high-performing, reliable, and scalable ML-native platforms. You will also serve as a technical leader within the Engineering team, helping cultivate a strong ML engineering culture and staying at the forefront of rapidly evolving AI technologies. This role reports to the Director of Engineering.


This is a role for someone who thrives at the intersection of cutting-edge AI research and production-grade engineering. The right fit is someone who can translate state-of-the-art methods into durable, enterprise-ready systems while understanding the requirements of clinical r...

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