Senior Principal Engineer, AI / ML

Edwards Lifesciences • Alton, IL

2d • $151,000 - $215,000

About The Position

Innovation starts from the heart. Our Advanced Innovation & Technology (AI&T) teams harness the imagination, courage, and resourcefulness to think beyond what’s currently possible, and create solutions for patients many years into the future. If you’re an early-stage innovator, then Edwards AI&T team is the place for you to take the next steps in your career. We’ll give you the tools and resources you need to create groundbreaking innovations that shape the future of structural heart technology. How you’ll make an impact: Enterprise AI Architecture, Platform Ownership, Strategy, Governance & Engineering Collaborate with leadership to develop and own enterprise AI architecture, design patterns, and standards across GenAI, LLM, and traditional ML platforms. Establish engineering guardrails and best practices for data pipelines, model lifecycle management, deployment, and AI system integration. Serve as the final technical authority for AI platform architecture, engineering decisions, and technology selection. Lead AI platform governance, partnering with Architecture Review Boards and enterprise change and product governance bodies. Ensure engineering excellence across AI codebases, models, and platforms, including documentation, testing, observability, security, and compliance. Drive the AI platform strategy and roadmap, incorporating emerging AI technologies where they deliver measurable business value. Define and track platform‑level metrics to demonstrate business value, performance, reliability, and cost efficiency. AI Solution Design & Delivery Plan and lead the end‑to‑end design, development, and deployment of complex AI/ML solutions at enterprise scale. Partner with business SMEs, product managers, data scientists, and engineering teams to translate complex business problems into robust AI solutions. Be accountable for the successful delivery of AI initiatives, ensuring solutions are production‑ready, scalable, and compliant. Drive architectural decisions across system integrations, deployment patterns, and operationalization. Plan and lead the design, development, and deployment of AI solutions at scale to solve more complex business problems in partnership with business SME's, product managers, data scientists, and other engineering teams. Technical Leadership & Mentorship Provide technical leadership, mentorship, and guidance to engineers and data scientists across the organization. Build and maintain robust data pipelines for training, testing, and evaluating various Large Language Model's (LLM) and/or traditional machine learning models and engineer solutions based on various AI/ML frameworks and libraries Set engineering quality bars and promote consistent best practices across AI teams. Manage and develop assigned team members, including coaching, performance feedback, and talent development. Partner with HR on hiring, performance management, and employee development. Provide technical leadership and mentorship to junior engineers and data scientists Technical & AI Enablement Contribute to system design and architectural discussions. Demonstrate understanding of distributed systems and AI workflows. Validate technical designs for scalability and maintainability. Stay current with AI, cloud, and engineering best practices. Create and manage program and project plans. Drive end-to-end delivery from ideation to launch. Coordinate across engineering, data science, and platform teams. Track risks, dependencies, and delivery status. Support product adoption and post-launch evaluation. Serve as a capability business subject matter expert, demonstrate expertise in business processes and capabilities. Determine operational feasibility by evaluating analysis, problem definition, requirements, solution development, and proposed solutions. Stay current with the latest GenAI and/or traditional AI/ML research and trends and incorporate them into our product offerings. Improve and optimize the performance of models, ensuring robustness, scalability, and efficiency. Ensure code and model development are well-documented and follow EW engineering practices.

Requirements

• Bachelor’s Degree plus 10 years’ experience in software development or engineering and solid performance working with cross-functional teams on enterprise level or complex/ novel system implementations -or- Master’s Degree plus 8 years of related experience
• Deep expertise in computer science, software engineering fundamentals, and defining enterprise-wide architecture and engineering standards.
• Proven experience designing, building, governing, and operating enterprise AI platforms, including data pipelines, model infrastructure, and AI applications.
• Strong proficiency in Python, modern software engineering practices, and leading AI/ML frameworks.
• Exceptional troubleshooting and problem‑solving capabilities across complex, distributed AI systems.

Nice To Haves

• Experience in regulated Healthcare and/or Manufacturing environments.
• Expert‑level experience with Palantir Technologies, including Foundry and AIP.
• Experience with Databricks Mosaic AI, MLflow
• Proven ability to influence across organizations and drive technical outcomes at scale.
• Prior experience in a principal‑level or enterprise technical leadership role owning AI platforms and standards
• Enterprise AI architecture, engineering standards, and governance
• Model, data, and platform engineering patterns and best practices
• AI platform strategy, roadmap, and evolution
• Technical direction for Palantir‑based AI, GenAI, and ML platforms
• Strong understanding of enterprise IT processes, architecture governance, and cross‑domain dependencies.

Responsibilities

• Collaborate with leadership to develop and own enterprise AI architecture, design patterns, and standards across GenAI, LLM, and traditional ML platforms.
• Establish engineering guardrails and best practices for data pipelines, model lifecycle management, deployment, and AI system integration.
• Serve as the final technical authority for AI platform architecture, engineering decisions, and technology selection.
• Lead AI platform governance, partnering with Architecture Review Boards and enterprise change and product governance bodies.
• Ensure engineering excellence across AI codebases, models, and platforms, including documentation, testing, observability, security, and compliance.
• Drive the AI platform strategy and roadmap, incorporating emerging AI technologies where they deliver measurable business value.
• Define and track platform‑level metrics to demonstrate business value, performance, reliability, and cost efficiency.
• Plan and lead the end‑to‑end design, development, and deployment of complex AI/ML solutions at enterprise scale.
• Partner with business SMEs, product managers, data scientists, and engineering teams to translate complex business problems into robust AI solutions.
• Be accountable for the successful delivery of AI initiatives, ensuring solutions are production‑ready, scalable, and compliant.
• Drive architectural decisions across system integrations, deployment patterns, and operationalization.
• Plan and lead the design, development, and deployment of AI solutions at scale to solve more complex business problems in partnership with business SME's, product managers, data scientists, and other engineering teams.
• Provide technical leadership, mentorship, and guidance to engineers and data scientists across the organization.
• Build and maintain robust data pipelines for training, testing, and evaluating various Large Language Model's (LLM) and/or traditional machine learning models and engineer solutions based on various AI/ML frameworks and libraries
• Set engineering quality bars and promote consistent best practices across AI teams.
• Manage and develop assigned team members, including coaching, performance feedback, and talent development.
• Partner with HR on hiring, performance management, and employee development.
• Provide technical leadership and mentorship to junior engineers and data scientists
• Contribute to system design and architectural discussions.
• Demonstrate understanding of distributed systems and AI workflows.
• Validate technical designs for scalability and maintainability.
• Stay current with AI, cloud, and engineering best practices.
• Create and manage program and project plans.
• Drive end-to-end delivery from ideation to launch.
• Coordinate across engineering, data science, and platform teams.
• Track risks, dependencies, and delivery status.
• Support product adoption and post-launch evaluation.
• Serve as a capability business subject matter expert, demonstrate expertise in business processes and capabilities.
• Determine operational feasibility by evaluating analysis, problem definition, requirements, solution development, and proposed solutions.
• Stay current with the latest GenAI and/or traditional AI/ML research and trends and incorporate them into our product offerings.
• Improve and optimize the performance of models, ensuring robustness, scalability, and efficiency.
• Ensure code and model development are well-documented and follow EW engineering practices.

Benefits

• Aligning our overall business objectives with performance, we offer competitive salaries, performance-based incentives, and a wide variety of benefits programs to address the diverse individual needs of our employees and their families.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior