Senior Scientific Software Engineer, Analytics and Workflows

The Opportunity

Genentech is seeking a talented and highly motivated Bioinformatics Software Engineer to join our newly established Computational Sciences Center of Excellence (CoE) within the Analytics and Workflows group. In this role, you will operate at the critical intersection of data science, biology, and software engineering, building scalable tools that bridge the gap between raw experimental data and meaningful biological interpretation. You will work alongside world-class computational biologists, data scientists, and research teams across gRED and pRED to advance drug discovery pipelines and deliver life-changing medicines to patients worldwide.

• Establish, optimize, and maintain reusable workflows, core libraries, and interactive visualization tools for the analysis and quality control of proteomics, genetics, and genomics data.
• Evaluate, refine, and productionize analytical pipelines that empower research scientists to interrogate complex biology and make data-driven pipeline decisions.
• Facilitate seamless data reuse, multimodal analysis, and downstream AI/ML initiatives by promoting standardized data models, metadata tracking, and centralized repositories.
• Deeply engage with computational scientists and domain researchers to translate complex analytical needs into robust, modular, and maintainable software components.
• Evaluate and combine open-source tools, commercial technologies, and custom in-house software into unified, reliable applications.
• Collaborate with interdisciplinary teams of software engineers, computational biologists, and machine learning scientists to build diverse programmatic and user-friendly interfaces.

Who you are

• Hold a PhD in Software Engineering, Computer Science, Bioinformatics, or a related quantitative field with at least 2 years of relevant experience, or a Master's degree with at least 5 years of relevant experience in a clinical, academic, or commercial research setting.
• Possess expert knowledge in at least one biological domain—such as multimodal single-cell, proteomics, or large-scale genetic analysis—with a demonstrated track record of rapidly identifying, diagnosing, and mitigating anomalous data or edge cases.
• Bring extensive hands-on experience developing robust software and analytical tools within modern Python and R data science ecosystems, frameworks, and web architectures.
• Demonstrate AI fluency by actively applying emerging computational technologies, modern ML frameworks, or agentic tooling to optimize scientific workflows and accelerate project deliverables.
• Have demonstrated success taking software projects through the full lifecycle—including requirements gathering, design, testing, continuous deployment, documentation, and long-term maintenance.

Preferred

• Experience designing and managing FAIR (Findable, Accessible, Interoperable, Reusable) data architectures, including robust data provenance, lineage tracking, and biological data cataloging.
• Prior professional experience working within a biotechnology, pharmaceutical, or drug discovery R&D environment.
• Proven ability to decompose large, ambiguous scientific problems into clean, modular components, working with high autonomy across concurrent project deadlines.
• Experience developing scalable web applications or interactive dashboards (e.g., Shiny, Streamlit, Dash, FastAPI) tailored for biological data visualization.

Location

• This role is based in South San Francisco and offers a hybrid schedule working 3 day per week on campus
• No relocation benefits are available for this posting