Lead Bioinformatics Engineer

Lead Bioinformatics Engineer
South San Francisco, CA

Who Are We?

Our company is based on the science of our founder, Stanley Qi, one of the original CRISPR co-inventors who then furthered the technology so that DNA does not need to be cut to accomplish gene regulation. Instead, we regulate the epigenome to suppress and activate multiple genes simultaneously. We are further evolving the platform and leveraging its strengths to address unmet medical needs. We are well funded and still in stealth mode with plans to emerge in 2022.

We are looking for exceptional team members who want an active role in building a rapidly growing biotech.

Roles and responsibilities:

  • Integrate with LIMS to automate and scale our laboratory’s operations.
  • Work with third-party vendors to build and maintain relationships.
  • Interface with wet lab scientists to build required pipelines and implement changes that will improve the system's overall efficiency.
  • Write and review bioinformatics pipelines.
  • Make design decisions, think about tradeoffs and propose technical solutions.
  • Establish the best Engineering practices and drive improvements in design, development and operations.
  • Mentor and guide junior engineers on design, coding, troubleshooting and operational excellence.
  • Make design decisions, think about tradeoffs and propose technical solutions.

Qualifications:

  • Bachelor's degree or equivalent experience in computer science, electrical engineering, bioinformatics, or a similar technical field.
  • 5+ years of work experience designing, developing, testing, and maintaining software.
  • 1+ years of experience as a mentor, tech lead OR leading an engineering team
  • Experience in integrations of internal and third-party applications.
  • Experience in the transfer of bioinformatics workflows from manual into high-throughput systems
  • 3+ years of programming experience in Python.
  • Experience with software engineering best practices: code quality, testing, performance optimization, development of research tools infrastructure.
  • Good engineering techniques and best practices (i.e. design control, FMEA, risk analysis, stress testing).
  • Experience working with a broad set of instruments and data: NGS, plate readers, imagers, flow cytometers, FACS, qPCR, and so on.
  • Experience creating and managing infrastructure in a Cloud Provider; for example Amazon Web Services, Google Cloud Provider, or Microsoft Azure.