Scientific Software Engineer Jobs
Scientific Software Engineer jobs are open across national laboratories, aerospace, pharmaceuticals, and research institutions, with specializations in numerical computing, high-performance computing, and scientific visualization, from early-career to principal and staff levels. See the openings below and apply to the ones that match your experience.
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Showing 5 of 39+ Scientific Software Engineer jobs
The Position
We’re passionate about delivering on Our Promise to improve the lives of patients and create healthier communities for all. We foster a culture of inclusivity, integrity and creativity while boldly pursuing answers to the world’s most complex health challenges and transforming society.
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
The expected salary range for this position based on the primary location of CA is $142,500 - $264,700. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
#LI-JD1
#ComputationCoE
#tech4lifeComputationalScience
#tech4lifeAI
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
The Position
We’re passionate about delivering on Our Promise to improve the lives of patients and create healthier communities for all. We foster a culture of inclusivity, integrity and creativity while boldly pursuing answers to the world’s most complex health challenges and transforming society.
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
The expected salary range for this position based on the primary location of CA is $142,500 - $264,700. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
#LI-JD1
#ComputationCoE
#tech4lifeComputationalScience
#tech4lifeAI
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
See All 39 Scientific Software Engineer Jobs
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Find JobsScientific Software Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Education
- Biotechnology & Pharmaceuticals
What Employers Look For
The qualifications that appear most often in scientific software engineer jobs.
- Bachelor's or master's degree in computer science, physics, math, or a related technical field
- Proficiency in Python, C++, or Fortran for numerical and scientific computing
- Experience with high-performance computing environments such as MPI, OpenMP, or CUDA
- Familiarity with version control systems and collaborative software development workflows
- Ability to read and interpret peer-reviewed scientific literature relevant to the domain
- Experience optimizing code for performance on large-scale data or simulation workloads
Tips for Your Scientific Software Engineer Job Search
Tailor your resume for computational depth
Hiring managers for scientific software roles scan for specific numerical libraries, parallelization frameworks, and domain knowledge. List the scientific domains you have coded for, such as fluid dynamics or genomics, alongside the languages and tools you used.
Show reproducible research contributions clearly
If you have written software that supports published research, name the paper or project and describe your code's role. Reviewers weigh peer-reviewed software contributions heavily, so a GitHub repository tied to a known dataset or simulation counts more than generic open-source work.
Apply early to roles that fit
Migrate Mate lists scientific software engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings by compute environment
Filter openings by the compute environment they describe, whether that is GPU clusters, cloud-based HPC, or on-premise supercomputers. Your experience translates differently to each, and matching your background to the stated environment makes your application stronger from the first screen.
Prepare a performance benchmark for interviews
Many scientific software engineer interviews include a code review or take-home exercise focused on runtime and memory efficiency. Have a concrete example ready that shows how you profiled a bottleneck, chose an algorithm or data structure, and measured the improvement in a real scientific workload.
Negotiate around publication and open-source rights
Some employers, particularly government contractors and national laboratories, have IP agreements that restrict publishing code or papers. Ask about these policies during the offer stage so you understand what contributions you can share publicly after the work is done.
Scientific Software Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most scientific software engineers?
The most active employers for scientific software engineers right now are QuEra Computing, Lynker, and BIOVIA, and the most openings are in Massachusetts, Maryland, and California, based on current listings on Migrate Mate as of November 2026. National laboratories, aerospace manufacturers, pharmaceutical companies, and climate research organizations are consistently among the most active hiring categories for this role.
How many scientific software engineer jobs are remote?
About 76% of scientific software engineer openings are fully remote or hybrid as of November 2026, though the share varies significantly by domain. Roles focused on data pipelines, bioinformatics, and climate modeling tend to offer more remote flexibility, while positions tied to physical instruments, secure government facilities, or on-site supercomputer clusters typically require in-person work.
How do you become a scientific software engineer?
Start by building strong foundations in both a scientific domain and software engineering. Study a quantitative field such as physics, biology, or engineering alongside computer science coursework that covers algorithms and numerical methods. Contribute to open-source scientific projects or reproduce published simulations to build a portfolio. Practical experience writing production-quality code in a research or laboratory setting is what moves candidates from graduate school into professional roles.
How do you get a scientific software engineer job with little experience?
Focus on research assistant or junior developer roles within university labs, national laboratory internship programs, or government-funded research groups, since these positions are specifically designed for candidates early in their careers. Build a portfolio that demonstrates you can write clean, documented, testable code for a real scientific problem, even if the project originated in a class or personal research interest. Contributions to established open-source scientific libraries also help establish credibility with experienced reviewers.
What does the scientific software engineer interview process look like?
Most processes begin with a technical phone screen covering programming fundamentals and relevant domain knowledge, followed by a take-home assignment or live coding exercise focused on numerical algorithms, data structures, or performance optimization. Later rounds typically include a system design discussion specific to scientific workflows and a conversation with researchers or scientists who will use the software. Some employers, particularly national laboratories, also require a background check and security clearance review before extending an offer.
Where can I find and apply to scientific software engineer jobs?
You can find and apply to scientific software engineer jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your domain experience and technical skills, then apply directly to each one that fits.
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