Senior Principal Machine Learning Engineer

About the role

The Sr. Principal ML Engineer will lead a team focused on enabling Data and AI/ML solutions and products across Transcarent, with a particular focus on the ML platform supporting the WayFinding™ experience.

Responsibilities

• Set technical direction with full autonomy, identifying systemic issues before they become crises, defining pragmatic architecture, and moving fluidly between hands-on execution and high-level design to unblock the initiatives that matter most.
• Partner closely with engineering leadership, product, and cross-functional stakeholders to translate ambiguous business problems into scalable technical solutions.
• Serve as a multiplier for the broader engineering organization through mentorship, design review, and technical influence.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 12+ years of professional software/data engineering experience, including significant time operating as a senior individual contributor at Principal level or above.
• Expert-level command of data engineering fundamentals: distributed data processing (Spark), stream and batch pipeline design, data warehouse/lakehouse architecture, and ELT/ETL patterns.
• Strong ML engineering proficiency, including feature engineering, model training and evaluation, deployment, and production monitoring.
• Hands-on experience with modern GenAI and LLM workflows, including RAG architectures, fine-tuning, prompt engineering, and responsible AI practices.
• Cloud-native platform fluency across one or more major providers (AWS, GCP, Azure), including managed data and ML services.
• Proficiency in Python and SQL as primary languages; comfort with Go, Java, or equivalent as needed.
• Demonstrated ability to lead complex, cross-functional technical initiatives from ambiguity through production without relying on organizational authority.
• Excellent written and verbal communication skills, with a track record of influencing senior technical and non-technical stakeholders.

Qualifications

• Experience with key ecosystem tools such as Databricks, dbt, Kafka, and MLflow.
• Experience in healthcare, benefits, or another regulated, compliance-sensitive industry.
• Track record of applying GenAI tools as a velocity and quality multiplier for yourself and your team.
• Experience defining data governance, lineage, and observability frameworks at platform scale.
• Prior experience mentoring senior engineers or informally leading technical communities of practice.