MedTech Software Safety Engineer — Assessment Specialist

Scarlet

Greater London

Hybrid

GBP 70,000 - 110,000

Full time

44 hours ago
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Job summary

Scarlet, based in the United Kingdom, is seeking a Software Safety Engineer to assess software lifecycle processes and regulatory documentation for medical device software. You will collaborate with product, engineering and applied machine learning teams to improve tools and surface safety risks and evidence gaps for rigorous certification decisions.

Ideal candidates have a CS degree and 4+ years in safety-critical environments, with strong communication skills and experience in software

Qualifications

  • A degree in computer science or a related discipline.
  • Four or more years’ experience in medical device or other safety-critical product manufacturing, auditing or research, including two or more years’ experience developing safety-critical software.
  • Practical experience with software development fundamentals, including lifecycle processes, verification & validation, configuration management and cybersecurity.
  • Exceptional written and verbal communication skills.

Responsibilities

  • Assess software lifecycle processes and technical documentation submitted by our customers.
  • Screen and action regulatory insights from the latest research, standards and guidance.
  • Work with our product, engineering and applied machine learning teams to improve our systems.
  • Work with our market access team to expand Scarlet's responsibility to new jurisdictions and certifications.
  • Create content to explain complex regulatory topics to customers and prospects.
  • Provide regulatory insights to prospects and customers.

Skills

Software safety
Regulatory knowledge
Communication skills

Education

Bachelor's degree in Computer Science

Job description

Scarlet, based in the United Kingdom, is seeking a Software Safety Engineer to assess software lifecycle processes and regulatory documentation for medical device software. You will collaborate with product, engineering and applied machine learning teams to improve tools and surface safety risks and evidence gaps for rigorous certification decisions.

Ideal candidates have a CS degree and 4+ years in safety-critical environments, with strong communication skills and experience in software

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