Support computational biologists and data scientists by building robust systems for machine learning workflows and enhancing research capabilities in cancer detection.
Partner with research teams to identify computational pain points or limitations in performing computational experiments and analyses.
Design, build, and evolve software which usefully extends research capabilities, including infrastructure for distributed ML training and evaluation on large controlled genomic datasets.
Develop tools and processes that ensure GxP-compliant testing, patchability, and inference reproducibility for classifiers that are promoted to production use.
Develop and maintain the research team’s software environment, including tools to assess the health, performance, and cost of the system.
These summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion.
5+ years of experience developing software supporting machine learning, scientific computing, or large-scale data processing systems
Strong programming skills in Python and a systems-level language such as Golang (preferred), Java, C#, C++, etc.
Experience working with modern machine learning frameworks such as PyTorch or TensorFlow
Experience with Distributed Computing paradigms (Spark, Ray, Flink, Beam, etc.)
A commitment to high-quality professionally engineered software
Strong communication skills with the ability to help developers from a wide range of software development backgrounds
BS in Computer Science, Engineering, Bioinformatics, or a related field, or equivalent practical experience
Good understanding of container orchestration through Docker and cloud technologies.
Experience with scientific computing tools: NumPy, Jupyter, R Notebook, etc.
Experience with techniques used in modern AI (including LLM) training
Experience with whole genome sequencing, whole exome sequencing, bisulfite sequencing, and/or whole transcriptome sequencing data
Practical experience setting up continuous integration systems, along with expertise in at least one build tool (e.g. Bazel (preferred), Buck, Maven, Gradle)
Familiarity with AWS services, best practices, and security
Advanced degree (MS or PhD) in computer science, engineering, bioinformatics or a related discipline
The expected, full-time, annual base pay scale for this position is $190k-$255k.
GRAIL is a healthcare company focused on advancing early cancer detection through innovative technologies. We leverage next-generation sequencing and large-scale clinical studies, combining expertise from scientists, engineers, and physicians to tackle the challenges of cancer care.
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