Next-generation DNA sequencing platform with embedded systems and ML-driven workflows
Element Biosciences builds hardware and software for DNA sequencing, combining embedded Linux, FPGA, GPU, and C++ on the instrument side with Python ML stacks (PyTorch, scikit-learn, Seurat, Scanpy) for data analysis. The tech shape—low-level systems engineering paired with bioinformatics tooling—reflects a vertically integrated product. Hiring is heavily weighted toward engineering and research (9 of 21 open roles) while support, logistics, and QMS maturation dominate the pain-point list, signaling scaling friction in manufacturing and field operations.
Element Biosciences designs next-generation sequencers and bioinformatics platforms for research labs and genomics facilities. Founded in 2017 and headquartered in San Diego, the company operates across the full stack: instrument design (FPGA, GPU, embedded systems), sequencing chemistry, and downstream analysis software (using established tools like GATK, Seurat, and Scanpy). The 201–500 person organization is actively scaling globally, with hiring in the United States, Netherlands, Japan, and China. Current operational priorities include beta-testing at customer sites, improving support KPIs, and navigating ISO 13485 compliance and electromagnetic compatibility standards.
Embedded Linux, FPGA, GPU, C++, Python (PyTorch, scikit-learn, Pandas), AWS, Docker, MATLAB, and bioinformatics tools (GATK, Seurat, Scanpy, HPLC). Salesforce and NetSuite handle CRM and ERP.
High-performance instrument platform development, multiomics data integration, LLM-based user workflows, customer beta testing and training, and expanding distribution in Asia-Pacific markets.
Element Biosciences's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.