SandboxAQ

SandboxAQ

Manager of Clinical Research, AQMed

Palo Alto, California · Vp

Sponsorship not specifiedDetected 50 days ago
GCPMachine LearningData ScienceEpicClinical TrialsClinical ResearchFDA RegulatoryMedical DevicesResearchLeadershipCommunicationCollaboration

About the role

  • The team operates at the intersection of regulated medical device development and fast-paced startup innovation, with a strong emphasis on quality, scientific rigor, and patient safety.
  • You will inherit a meaningful foundation - established processes and early clinical work already underway - and take it to the next level.
  • We are looking for a resourceful, deeply experienced clinical operator who thrives in ambiguity and moves with urgency.

Responsibilities

  • Own end-to-end execution of AQMed's clinical study portfolio, from feasibility through pivotal and across the US, Europe, and Asia.
  • Develop and maintain clinical study plans, protocols, budgets, agreements, timelines
  • Lead site identification, qualification, initiation, monitoring, and close-out across multi-center, multi-geography studies.
  • Select, onboard, and manage external clinical consultants and/or CRO partners
  • Build and sustain trusted relationships with clinical investigators, coordinators, and hospital administration at each study site.
  • Drive enrollment with creativity and urgency

Requirements

  • Strong working knowledge of 21 CFR Parts 812/820, ISO 14155, EU MDR.
  • Exceptional organizational and program management skills - you can hold 10 moving pieces without dropping any.
  • You bring proven multi-center trial leadership, global site management experience, and the judgment to make smart and data-driven decisions.

Skills

  • Familiarity with FDA De Novo, SaMD regulatory pathways, and AI/ML-based medical device submissions.
  • Guidance for candidates on using AI Tools in interviews https://www.sandboxaq.com/ai-in-interviews

Compensation

  • Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.

Benefits

  • Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
  • Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.

Company info

  • Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.
  • We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued.
  • Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.
  • We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties.
  • At SandboxAQ, we've cultivated an environment that encourages creativity, collaboration, and impact.

Equal opportunity

  • All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.
  • Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles.
  • If you need such an accommodation, please let a member of our Recruiting team know.
  • Read: Guidance for candidates on using AI Tools in interviews https://www.sandboxaq.com/ai-in-interviews

Visa & Work Authorization

  • ill receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status

This listing is sourced directly from SandboxAQ's careers page and normalized into a canonical job model.