Principal Scientist, AI & ML for Healthcare Innovation

Edwards Lifesciences Gruppe; Irvine (CA); On-site; USD 132,000 - 186,000; Full time

Benefits offered by this job

Competitive salary

Performance incentives

Benefits package

Job summary

Edwards Lifesciences in California seeks a Principal Scientist to define the scientific and technical direction of AI across the structural heart journey. You will evaluate new technologies, incubate capabilities, and guide teams building AI-enabled products in regulated healthcare environments.

You will lead scalable AI solutions with cross‑functional teams, develop domain-specific foundation models for clinical data, advance generative and multimodal AI, ensure safety and fairness, mentor

Qualifications

• Bachelor’s degree plus 6 years of AI/ML engineering experience.
• Proven experience designing, training, and validating ML models end to end.
• Deep breadth across NLP/agentic AI, computer vision, time-series or computational modeling.

Responsibilities

• Lead scalable AI solution design with cross-functional partners.
• Develop domain-specific foundation models from clinical data.
• Research generative and multimodal AI techniques.
• Ensure models meet safety, fairness, and real-world performance.
• Mentor junior engineers and collaborate with regulatory teams.

Skills

NLP/Agentic AI

Computer vision

Time-series modeling

Computational modeling

Python programming

Regulated healthcare/ SaMD

Education

Bachelor's degree in CS/EE/related

MS/PhD in CS/ML/biomedical engineering

Tools

PyTorch

TensorFlow

Hugging Face

LangChain

LlamaIndex

OpenCV

NumPy

scikit-learn

Databricks

Snowflake

Azure

AWS

Job description

Edwards Lifesciences in California seeks a Principal Scientist to define the scientific and technical direction of AI across the structural heart journey. You will evaluate new technologies, incubate capabilities, and guide teams building AI-enabled products in regulated healthcare environments.

You will lead scalable AI solutions with cross‑functional teams, develop domain-specific foundation models for clinical data, advance generative and multimodal AI, ensure safety and fairness, mentor