Computational Biologist

Valthos Inc.

Valthos is an applied biological intelligence company. We build and deploy software and biological AI systems to safeguard humanity.

The same AI architectures that enable self-driving cars, land rockets with precision, and deliver expert-level reasoning are beginning to be deployed in biological design. To stay ahead, we must advance our arsenal of tools to capture and design against real-time sensitivities in nature’s evolving mutational landscape.

We are a group of mission-driven software engineers from Palantir and applied biological ML engineers from MIT’s Broad Institute and DeepMind making the latest advances in computational biology accessible in the real-world for federal and commercial use.

We are seeking a highly skilled Computational Biologist to bridge machine learning and biology by building robust data and evaluation frameworks for assessing and responding to biological threats, and for rapidly designing precision biologics.

The Role

Contribute to shaping and executing the Valthos-wide research and development roadmap

Identify large-scale biological datasets appropriate for training frontier biological models, and build workflows and infrastructure for processing these datasets

Design, build, and apply evaluation frameworks for rigorously assessing model performance on real-world problems in biological security

Design wet-lab experiments to evaluate the efficacy and real-world utility of designed biologics

Collaborate closely with AI engineers to design and train models tailored to tasks in biological security and precision biologics

Collaborate closely with software engineers to build and deploy tools for data analysis, including proper documentation and testing

Visualize and communicate results clearly within Valthos and externally

Work with customers and external collaborators to understand their needs and effectively represent Valthos

Embrace continuous learning in both technical and non-technical areas across Valthos

Stay up-to-date on state-of-the-art methods at the intersection of AI and biology

Qualifications (required)

Experience analyzing biological datasets, ideally sequence-based modalities (e.g., genomic, protein, metagenomic)

Experience planning and running in silico computational biology experiments

High proficiency in Python and its scientific package ecosystem

Experience with bioinformatics sequence analysis tools (e.g., aligners)

Experience with cloud computing platforms (e.g., AWS)

Qualifications (preferred)

Proven ability to design, implement, and evaluate novel methods in computational biology

Experience working with experimental biologists to plan and interpret the results of wet-lab experiments

Experience with ML-centric bioinformatics and structure-based tools (e.g., AlphaFold)

Knowledge of biological databases (e.g., NCBI)

Experience with machine learning model training and evaluation

Contributions to open-source projects

If there is a fit, we'll schedule two technical interviews. The final step is an onsite in our office, where you'll work on a small project, discuss ideas, and work with the wider team.