Principal ML Engineer

Principal ML Engineer

Thank you for your interest in joining Solventum. Solventum is a new healthcare company with a long legacy of solving big challenges that improve lives and help healthcare professionals perform at their best. Guided by empathy, insight, and clinical intelligence, we collaborate with the best minds in healthcare to address our customers' toughest challenges.

At Solventum, people are at the heart of every innovation we pursue. We pioneer game‑changing innovations at the intersection of health, material and data science to improve patient lives while enabling healthcare professionals to perform at their best.

As a Principal ML Engineer, you will lead the technical architecture and engineering strategy for integrating sophisticated AI into high‑stakes Healthcare Information Systems (HIS). Your focus will be on reliability, system performance, and automated scalability, rather than hype.

Your mission is the engineering of the ecosystem: architect robust MLOps pipelines and cloud infrastructure that move models from experimental notebooks into mission‑critical clinical environments.

• Production Lifecycle: Lead the design and implementation of end‑to‑end ML life cycles, focusing on automated CI/CD pipelines, model versioning (MLflow/DVC), and reproducible experimentation.
• Inference at Scale: Architect high‑performance serving layers for both LLMs and classical models, ensuring low‑latency and high‑availability in a secure healthcare cloud environment.
• Agentic Orchestration: Build the underlying infrastructure for agent‑based reasoning systems, ensuring these workflows are traceable, auditable, and integrated into existing HIS.

• Data Reliability: Design robust data pipelines (ETL/ELT) to process healthcare‑specific formats (FHIR, HL7, DICOM) into high‑quality features for real‑time and batch inference.
• Hybrid Infrastructure: Manage and optimize cloud‑native infrastructure (AWS/Azure/GCP) using Infrastructure as Code (Terraform/Pulumi) to support heavy compute workloads.
• System Integrity: Implement comprehensive monitoring and observability frameworks to detect data drift, model decay, and system bottlenecks before they impact clinical outcomes.

• Engineering Authority: Serve as the lead architect for the ML platform, ensuring all systems are HIPAA/HITRUST compliant and follow "security‑by‑design" principles.
• Operational Excellence: Establish rigorous standards for code quality, containerization (Docker/Kubernetes), and system documentation across the engineering organization.
• Strategic Mentorship: Elevate the team by fostering a culture of "ML as Engineering," guiding junior engineers in building maintainable, modular, and scalable software.

To set you up for success in this role from day one, Solventum requires (at a minimum) the following qualifications:

• Bachelors Degree or Higher in Computer Science, Software Engineering, or a related technical field.
• 10+ years of experience in software engineering, with at least 6 years dedicated to deploying and maintaining large‑scale ML systems in production.
• MLOps & Cloud: Expert‑level experience with Cloud Providers (AWS/GCP/Azure) and orchestration tools (Kubernetes, Kubeflow, or Airflow).
• Engineering & Programming: Expert‑level Python and Java/Go (or similar), deep proficiency in backend frameworks and system design patterns.
• Data Engineering: Strong experience with Spark, Snowflake/Databricks, and building scalable feature stores.
• Applied AI: Hands‑on experience deploying Generative AI (LLMs) and Agentic frameworks (Lang Chain/Lang Graph) within a containerized microservices architecture.

• Hardware Optimization: Experience with GPU optimization, quantization, or specialized serving frameworks (vLLM, TGI).
• Master's or PhD in Computer Science, Software Engineering, or a related technical field is preferred.
• Security & Compliance: Deep understanding of cybersecurity best practices within regulated industries…