Lead ML Software Engineer - Remote Healthcare AI

Wiraa

United States

Remote

USD 180,000 - 240,000

Full time

5 days ago
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Benefits offered by this job

Comprehensive compensation package
Health and wellness benefits
Tuition assistance program
Professional growth opportunities
Mission-driven work environment

Job summary

Penn Medicine is seeking a Lead ML Software Engineer to join the PennDnA Data Science team. You will develop, implement, and maintain advanced ML software solutions, lead projects, and collaborate with clinicians, data scientists, and IT leaders to generate impactful healthcare insights.

The role emphasizes leadership, governance, scalable ML architectures, and end-to-end ML lifecycle management across on-prem and cloud environments.

Qualifications

  • Bachelor's in Computer Science or related field is required.
  • Minimum 5 years of software engineering experience developing and deploying ML models.
  • Proven track record of independently leading projects and collaborating with cross-functional teams.

Responsibilities

  • Provide strategic direction and technical leadership for ML software engineering initiatives.
  • Develop scalable, modular architectures for ML systems and CI/CD pipelines.
  • Integrate ML solutions with health system applications (e.g., Epic) and cloud/on-prem infrastructure.
  • Lead projects from concept to execution and mentor junior team members.
  • Stay current with ML tech trends and healthcare analytics to drive improvements.

Skills

5+ years software engineering
cross-functional leadership
lead projects independently

Education

Bachelor's in CS or related field
Master's in CS or related field

Job description

Penn Medicine is seeking a Lead ML Software Engineer to join the PennDnA Data Science team. You will develop, implement, and maintain advanced ML software solutions, lead projects, and collaborate with clinicians, data scientists, and IT leaders to generate impactful healthcare insights.

The role emphasizes leadership, governance, scalable ML architectures, and end-to-end ML lifecycle management across on-prem and cloud environments.

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