Responsibilities
- Translate research code and exploratory analysis into robust, scalable software modules for regulated medical devices at the core of GRAIL’s cancer detection products.
- Lead the design and implementation of verification strategies and automated tests for ML components, data pipelines, and bioinformatics software.
- Build and maintain automated testing infrastructure to support continuous verification of production and device software, ensuring test coverage, reproducibility, and compliance.
- Drive improvements in CI/CD pipelines for bioinformatics and ML workflows, ensuring fast, secure, and reproducible deployment of production and experimental code.
- Identify and implement high-performance, scalable solutions to improve the robustness, efficiency, and security of clinical and research bioinformatics pipelines.Follow GRAIL’s SDLC processes to ensure release quality, traceability, and compliance.
- Prototype novel tools and analytical methods to support quality assurance and interpretability of cancer signals across multiple data types.
- Engage with cross-functional teams (ML, bioinformatics, clinical, regulatory) to lead ambiguous or emerging projects, bringing clarity and direction through engineering leadership.
Preferred Qualifications
- Advanced degree (Master’s or PhD) in Computer Science, Bioinformatics, Computational Biology, or a related quantitative discipline.
- 5+ years of industry experience developing production-quality bioinformatics software, pipelines, or infrastructure.
- Demonstrated expertise in verification planning and automated testing for scientific or regulated software.
- Fluency in Python, with strong proficiency in at least one additional language such as Go, C++, or Java.
- Practical experience analyzing next-generation sequencing (NGS) data, with a focus on DNA methylation, epigenomics, or related genomics applications.
- Familiarity with bioinformatics file formats and toolchains (e.g., FASTQ, BAM, VCF; samtools, bcftools, Picard).
- Hands-on experience with cloud computing platforms (AWS, GCP, Azure) and familiarity with containerization (Docker/Kubernetes).
- Solid understanding of regulated software development lifecycles.
- Proven ability to independently lead projects, collaborate cross-functionally, and navigate ambiguity in a dynamic research or product development setting.
- Highly Preferred:
- Familiarity with workflow or pipeline frameworks, such as Reflow, Nextflow, Airflow, or similar.
- Experience with machine learning infrastructure, including model training orchestration, experiment tracking, and deployment workflows.
- Applied experience with statistical modeling, machine learning, or development of interpretability tools for biological data.
- Knowledge of reproducibility tooling (e.g., containerization, workflow versioning, dependency locking).
What We Do
GRAIL is a healthcare company whose mission is to detect cancer early, when it can be cured. GRAIL is using the power of high-intensity sequencing, population-scale clinical studies, and state-of-the-art computer science and data science to enhance the scientific understanding of cancer biology, and to develop and commercialize pioneering products.
Why Work With Us
Everything we do is guided by our mission to detect cancer early, when it can be cured. It’s the reason we’re here, and it’s no small task.
The right people make all the difference. That’s why we’re looking for those who strive to share their knowledge, contribute their skills, inspire each other and commit to something bigger than themselves.
Gallery
GRAIL Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
GRAIL has a variety of work types depending on the roles. Some are onsite like a lab role, others are hybrid and still others are remote. Hybrid is typically Tuesday and Thursday but leaders may be flexible depending on the role.











