Software Engineer- Biology Research

Software Engineer- Biology Research ROCGJP00030806

A leading biotechnology company is seeking a Software Engineer- Biology Research to join the Biology Research department. The successful candidate will develop software for our sequence-to-function models to deliver a high-quality Python package featuring robust test coverage, seamless installation, and a thoughtfully designed API. The ideal candidate is proficient in Python with substantial experience in software development, especially in developing maintainable and scalable codebases.

Software Engineer- Biology Research Pay and Benefits:

• Hourly pay: $35-$45/hr
• Worksite: Leading biotechnology company (South San Francisco, CA 94080 - Onsite, Open to remote candidates in the United States, Mutwork Pacific Time office hours, Candidates located in South San Francisco are preferred)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program
• 40 hours/week, 8 Month Assignment

Software Engineer- Biology Research Responsibilities:

• Refactor and optimize the existing DNA foundation model codebase to ensure maintainability, readability, and scalability.
• Develop and implement comprehensive testing strategies to achieve high test coverage.
• Design and build a robust, user-friendly API for internal sequence-to-function modeling applications.
• Integrate and implement new computational methods and modeling approaches as needed.
• Fine tune sequence-to-function models as needed.

Software Engineer- Biology Research Qualifications:

• 5+ professional software engineering experience.
• Proficiency in Python with substantial experience in software development, especially in developing maintainable and scalable codebases.
• Demonstrated expertise with PyTorch.
• Experience working with single-cell omics data and familiarity with established DNA/RNA sequence modeling frameworks (e.g., Enformer, Borzoi) and scverse ecosystem tools.
• Self-motivated with excellent communication skills and enthusiasm for contributing to computational biology and software development efforts.
• Strong track record of applying software engineering best practices, including version control (Git), comprehensive testing, modular design, and appropriate abstraction levels.