Senior AI/ML Engineer (Hybrid)
Mayo Clinic21 days ago
Rochester, MN, USASenior
Responsibilities
- Lead component design, development, integration, and standardization for AI-driven healthcare solutions.
- Develop and deploy end-to-end AI/ML solutions using techniques including deep learning, natural language processing, computer vision, and large language models.
- Establish evaluation methodologies and performance metrics for AI effectiveness, usability, and real-world healthcare impact.
- Oversee systems used to develop and deploy AI solutions, including automated development and release tools and associated CI/CD pipelines.
- Apply quality-system, risk-mitigation, verification, validation, regulatory, and compliance practices to digital health technology products.
- Collaborate with clinicians, UX designers, product managers, IT professionals, and external partners to translate clinical needs into AI solution designs.
- Provide consultative services, explain complex technical findings to nontechnical stakeholders, and train healthcare staff on AI tools and technologies.
- Mentor junior engineers and contribute to AI methods, development standards, and deployment best practices.
Requirements
- Bachelor's degree in engineering, computer science, mathematics, health science, or a related field with 6 years of experience, or a master's degree in one of these fields with 4 years of experience.
- Extensive experience applying AI and machine learning in production healthcare environments or similarly regulated or technology-focused industries.
- Experience leading complex projects and technical or quantitative teams in regulated environments.
- Expertise in AI/ML techniques and frameworks, including deep learning, natural language processing, and Generative AI.
- Proficiency with tools such as Python, TensorFlow, PyTorch, scikit-learn, and Keras.
- Experience with cloud infrastructure, software development tools, large heterogeneous data sets, data engineering, data science, AI engineering, and MLOps practices.
- Knowledge of healthcare domains including clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards.
- Experience with systems or quality engineering, risk management files, verification and validation strategies, user-centered design, human factors engineering, and usability testing.
- Strong collaboration, communication, consultation, education, technical reporting, initiative, mentoring, and time-management skills.
- Preferred: Ph.D. or other doctorate and experience developing new healthcare AI methods and technologies.
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