Data Selection And Quality Evaluation For Biological Foundation Models (AI)

Location: Palo Alto, California; candidates are expected to primarily work from office locations. Availability to collaborate across US and Europe is required, with meetings from 8am PT to 7pm CET.

Compensation: $135K–$240K annually, plus bonus and equity.

Company

hirify.global develops AI and biological software for the rational design of medicines and biotechnologies by combining molecular biology, machine learning, and software engineering.

What you will do

• Develop statistical and computational methods to evaluate assay quality, reproducibility, and experimental variation.
• Identify and investigate bias, batch effects, and measurement artifacts in biological datasets.
• Design and analyze large-scale biological experiments for machine learning training and evaluation data.
• Partner with experimental scientists to improve assay design, controls, and data collection strategies.
• Collaborate with machine learning researchers to assess how experimental design affects model training and evaluation.
• Analyze, visualize, and communicate findings across scientific and engineering teams.

Requirements

• PhD in computational biology, systems biology, genomics, bioengineering, biostatistics, biophysics, or a related quantitative discipline, or equivalent practical experience.
• Track record of analyzing complex biological datasets and translating computational insights into experimental validation or new data collection.
• Strong foundation in experimental design, statistical analysis, and quantitative reasoning.
• Deep understanding of experimental variability, batch effects, and assay artifacts in biological data.
• Proficiency in Python and common scientific computing libraries.
• Ability to work with US and European colleagues and primarily work from office locations.

Nice to have

• 3+ years of post-PhD experience in computational biology, biostatistics, or a related field.
• Experience connecting experimental outcomes to machine learning model development and evaluation.

Culture & Benefits

• Antedisciplinary environment focused on learning across biology, machine learning, and software engineering.
• 30 days of paid vacation per year.
• Comprehensive health insurance for US-based employees.
• 401(k) with company match for US-based employees and Direktversicherung for German employees.
• Quarterly company-wide retreats, wellness benefits, and budgets for office visits in Berlin, Palo Alto, or Switzerland.
• Learning and development budget plus onboarding support from a buddy.