Engineering Manager: ML/Data Platform & Device (Stock)

Meet Life Sciences

San Francisco (CA)

On-site

USD 180,000 - 240,000

Full time

45 hours ago
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Benefits offered by this job

Stock options
401(k) with matching

Job summary

Meet Life Sciences is partnering with a stealth neurotechnology company in San Francisco to build a data-intensive platform that translates research into reliable, commercially ready software products. The role focuses on leading a small team across data-heavy applications, ML workflows, and device integrations.

You will shape technical strategy, drive day-to-day execution, and mentor engineers to deliver robust, scalable features in a highly collaborative, fast-moving environment.

Qualifications

  • Experience delivering medical software across the full product lifecycle.
  • Experience planning and delivering multi-person software projects.
  • Proven track record mentoring engineers.
  • Strong understanding of ML pipelines, device integration and distributed architectures.
  • Excellent communication across research, product and quality.

Responsibilities

  • Introduce engineering best practices focused on quality, modularity, usability.
  • Mentor engineers with regular feedback, coaching and technical guidance.
  • Design and implement core server-side modules and integrations.
  • Collaborate with Quality and Regulatory to produce documentation.
  • Translate research concepts into production-ready software.

Skills

Software leadership
ML pipelines
Device integration
Distributed systems
Communication skills

Tools

Cloud platforms
ML workflows

Job description

Meet Life Sciences is partnering with a stealth neurotechnology company in San Francisco to build a data-intensive platform that translates research into reliable, commercially ready software products. The role focuses on leading a small team across data-heavy applications, ML workflows, and device integrations.

You will shape technical strategy, drive day-to-day execution, and mentor engineers to deliver robust, scalable features in a highly collaborative, fast-moving environment.

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