Senior Principal Machine Learning Engineer

Transcarent is hiring a Senior Principal Machine Learning Engineer to set technical direction across its Data and AI organization. The role combines hands-on engineering and architecture for data platforms, ML systems, and GenAI, while advancing cross-team initiatives and technical practices.

Responsibilities:

• Own the technical architecture and roadmap across our data platform, warehouse, ELT pipelines, ML systems, and GenAI components
• Independently identify, scope, and resolve systemic architectural issues across the Data and AI/ML stack
• Contribute directly to the codebase with high velocity, moving fluidly between implementation and high-level designBring the energy needed to transform health and care, and move and adapt rapidly
• Plan and deliver complex initiatives spanning multiple teams and systems, proactively surfacing risks and decisions to leadership
• Embed data governance, quality, lineage, and observability practices into every initiative from the outset
• Partner with cross-functional stakeholders to clarify requirements and own the technical path from framing through delivery
• Raise the technical bar across the organization through code reviews, design feedback, and direct coaching
• Design fault-tolerant distributed data pipelines with checkpointing, replay, and schema evolution
• Establish end-to-end data lineage, data quality SLAs, and automated data contract enforcement across platform initiatives

Requirements:

• 12+ years of professional software/data engineering experience, including significant time as a senior IC at Principal level or above
• Expert-level command of data engineering fundamentals: distributed processing (Spark, Flink), stream/batch pipelines, and data warehouse/lakehouse architecture
• Strong ML engineering proficiency across the model lifecycle, from training and evaluation through deployment and production monitoring
• Hands-on experience with modern GenAI/LLM workflows, including RAG architectures, fine-tuning, and prompt engineering
• Cloud-native platform fluency (AWS, GCP, or Azure) and proficiency in Python and SQL
• Demonstrated ability to lead complex, cross-functional technical initiatives without relying on organizational authority
• Excellent written and verbal communication skills with both technical and non-technical audiences
• Experience tuning warehouse/lakehouse performance through partitioning, query optimization, and workload isolation
• Experience implementing model drift detection, reproducible ML deployments, and production rollback strategies
• Experience evaluating RAG quality using retrieval metrics, groundedness testing, and automated regression gates
• Experience with Databricks, dbt, Kafka, and MLflow or equivalent ecosystem tools
• Experience in healthcare, benefits, or another regulated, compliance-sensitive industry
• Track record of using GenAI tools as a velocity and quality multiplier
• Experience defining data governance and observability frameworks at platform scale
• Prior experience mentoring senior engineers or leading technical communities of practice