
Helical is focused on providing open-source bio foundation models, particularly in the realm of single-cell analysis, enabling scientists to leverage advanced AI tools for their research. Their…

Helical is focused on providing open-source bio foundation models, particularly in the realm of single-cell analysis, enabling scientists to leverage advanced AI tools for their research. Their…
What they do: Platform for Bio Foundation Models enabling in-silico experiments for drug discovery and R&D
HQ: Luxembourg
Stage / funding: Seed (closed Jun 28, 2024)
Founders: Mathieu Klop; Maxime Allard; Rick Schneider
Drug discovery and pharmaceutical R&D using AI-driven in-silico experiments
2024
Biotechnology Research
Reported seed round with seven investors
“Has participation from early-stage investors and angel/backer set including Frst and named investors”
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Drug discovery still relies on wet labs: slow, expensive, and constrained by physical trial-and-error. Helical is changing that.
We build the application layer that makes Bio Foundation Models usable in real-world drug discovery, enabling pharma and biotech teams to run millions of virtual experiments in days, not years. Today, leading global pharma companies already use Helical, and we’re at the start of a highly ambitious growth journey.
We’re a founder-led, talent-dense team building a category-defining company from Europe. We care deeply about the quality of our work, move fast, and expect ownership. If you’re excited by complexity, real responsibility, and shaping how a company actually operates as it scales, you’ll feel at home here.
About the role
As a Software Engineering Intern, you’ll design and implement workflows for running Helical models at scale. You’ll work with technologies like Docker, Apache Airflow, Jupyterhub, MLflow, AWS, helping us improve the reliability, scalability, and observability of our machine learning pipelines.
You’ll collaborate closely with our AI infrastructure engineers to streamline how Helical’s Python-based modeling workflows are executed, monitored, and scaled in containerized environments.
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