Biomedical ML Engineer: Foundation Models & Pipelines

Abundance Network

United States

Sur place

USD 120 000 - 180 000

Plein temps

Il y a 6 jours
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Résumé du poste

Stanford University is seeking a Machine Learning Engineer to support advanced technical research within the Weill Cancer Hub. This role will focus on developing and applying AI and machine learning methods for biomedical and clinical applications, with an emphasis on rigorous evaluation in real-world settings.

Reporting to technical leadership and collaborating with senior faculty, you will build end-to-end data pipelines and software infrastructure for ML research.

Qualifications

  • Bachelor’s degree in engineering, science, or related field with relevant experience.
  • Strong knowledge of advanced scientific or engineering principles.
  • Ability to oversee instrumentation installation and manage complex projects.

Responsabilités

  • Support complex scientific and research programs; analyze data and oversee experiments.
  • Collaborate with scientists and engineers to optimize equipment and system designs.
  • Troubleshoot issues and resolve routine problems for scientists and engineers.
  • Lead or supervise technicians and staff in the group.
  • Ensure health and safety policies are communicated and enforced.
  • Plan and implement scientific or engineering initiatives toward project goals.

Connaissances

Advanced science
Engineering principles
Instrumentation installation
Cross-disciplinary collaboration
Project leadership

Formation

Bachelor’s degree in engineering or science

Description du poste

Stanford University is seeking a Machine Learning Engineer to support advanced technical research within the Weill Cancer Hub. This role will focus on developing and applying AI and machine learning methods for biomedical and clinical applications, with an emphasis on rigorous evaluation in real-world settings.

Reporting to technical leadership and collaborating with senior faculty, you will build end-to-end data pipelines and software infrastructure for ML research.

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