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Prima Mente · 2 weeks ago

GPU Accelerated Bioinformatics Engineer

San Francisco

Full-time

Onsite

Mid, Senior Level

Prima Mente is a frontier biology AI lab focused on generating data and building biological foundation models. They are seeking a GPU Accelerated Bioinformatics Engineer to architect and build scalable production pipelines for processing multi-omics data, optimizing performance and collaborating with AI and experimental teams.

Artificial Intelligence (AI)BiotechnologyNeuroscience

H1B Sponsored

Responsibilities

Design and implement GPU-native bioinformatics pipelines using Flyte and/or Nextflow for multi-omics data processing at scale (1000+ samples)

Optimising cost and performance, leveraging GPU acceleration where it matters

Work with experimental and machine learning teams to confirm and refine computational findings, and to ensure processing aligns with model needs

Cloud infrastructure

Develop and manage specific external research collaborations with academic and industrial partners

Qualification

GPU computingCloud computingBioinformatics pipelinesMulti-omics dataWorkflow managersData engineeringOperational software engineeringData wranglingPythonRJulia

Required

Knowledge of GPU computing backbone, whether directly through GPU-accelerated bioinformatics (e.g., NVIDIA Parabricks, Clara, Rapids, etc.) or through the ability to identify GPU vs. CPU optimisation in other contexts

Operational software engineering skills: the ability to write high-quality code to be the backbone of our software stack

Strong working knowledge with cloud computing environments, including but not limited to AWS and GCP

First-hand deep experience with at least 2-3 large omics types (genomics, transcriptomics, chromatin accessibility, DNA methylation, histone modifications profiling, etc.)

Experience with end-to-end tools used to process multi-omic data from raw data all the way to analytical outputs. Good working knowledge of workflow managers (e.g., Flyte, Nextflow, Snakemake)

Familiar with data wrangling, analysis, and visualisation libraries using Python (preferable), R or Julia

Strong data engineering knowledge, including but not limited to experience with Spark, Hadoop, NoSQL