# Member of Technical Staff - Computational Biologist at Valthos > Onsite · United States · Staff · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Avalthos%3Add6c0d36-e5ae-4ff5-9d5a-34b562a5e694 (read 2026-11-10). ## Facts (observed) - Company: [Valthos](https://alderhq.app/companies/valthos) - Location text: New York; San Francisco - Where it can be done from (inferred): Onsite · United States (evidence: "Location: New York; San Francisco") - Posted: 2025-08-29 (437 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-07 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/valthos/dd6c0d36-e5ae-4ff5-9d5a-34b562a5e694 - Skills listed (inferred): Python, AWS ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (New York, n 273): p25 $200k, median $234k, p75 $270k ## Description (the employer's text) ### 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Avalthos%3Add6c0d36-e5ae-4ff5-9d5a-34b562a5e694 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.