Principal Platform Bioengineering & Assay Development

Parallel Bio•San Francisco, CA

17d•$178,000 - $197,000•Onsite

About The Position

As Principal Scientist, you will lead the science at Parallel Bio’s San Francisco site. You will manage and develop scientists and research associates, set experimental strategy, and make scientific decisions about where to invest experimental effort while remaining hands-on at the bench for difficult problems. Your initial scientific focus will be to deepen understanding of how organoid models behave across donors, conditions, and operators; build reference data and controls that support confident interpretation; and bring rigor to site workflows. You will own assay development and maturation, technology transfer from R&D, control strategy, characterization, optimization, and readiness for routine platform execution. You will also lead the scientific work for external partner programs, from experimental design through rigorous interpretation and data delivery. The role spans scientific leadership, assay and process development, technology transfer and platform readiness, scale-up and robustness, and cross-functional platform development. You will establish frameworks, criteria, controls, documentation, and evidence needed to move assays from scientific concepts to reliable, scalable workflows and routine external execution. You will work closely with R&D, Process Development, Technical Operations, automation, hardware, software, and data teams. Parallel Bio is building human-first drug discovery using organoids and AI. The company describes its platform as 87% concordant with clinical patient data and says it is used by pharmaceutical partners, including three Fortune 500 companies. The company states that its mission is to replace animal models with scalable human biology and change how medicines are discovered.

Requirements

Ph.D. in Immunology, Cell Biology, Biology, Bioengineering, Biomedical Engineering, Molecular Biology, or a related discipline; equivalent combinations of education and experience will also be considered.
Typically 10 to 15 or more years of relevant experience developing complex biological assays, models, and platforms.
Demonstrated experience in several of the following areas: deep immunology expertise and hands-on work with complex human in vitro models, organoids, primary immune cells, or advanced mammalian cell culture.
Directly managing bench scientists, setting scientific direction, conducting data reviews, and developing scientific judgment in a team.
Building biological systems from 0 to 1 and adapting them to automated or higher-throughput platforms.
Assay development, characterization, optimization, and technology transfer.
Identifying and controlling biological and technical sources of variability.
Developing assays or processes for automated or high-throughput environments.
Translating early-stage R&D methods into robust workflows used by other scientists or operational teams.
Establishing controls, acceptance criteria, reference standards, or system-suitability approaches for biological assays.
Leading technically complex investigations and experimental troubleshooting.
Ability to reconcile competing scientific interpretations while maintaining healthy technical disagreement.
Hands-on experimental expertise and the ability to set scientific strategy while personally engaging at the bench.
Ability to bring structure to immature technologies while working comfortably with ambiguity.

Nice To Haves

Significant experience developing organoids, immune-cell assays, advanced human cell models, or other highly variable biological systems.
Experience scaling biological workflows onto automated laboratory platforms.
Experience with Design of Experiments, process characterization, capability analysis, or Quality by Design approaches.
Experience in regulated, quality-controlled, or highly documented scientific environments.
Experience supporting pharmaceutical or biotechnology partners and translating external scientific questions into executable platform workflows.
Experience partnering deeply with robotics, automation, software, data science, or machine-learning teams.

Responsibilities

Lead the scientific team at the San Francisco site, including hiring, managing, and developing scientists and maintaining high standards for experimental rigor and pace.
Set scientific direction and experimental strategy for the platform and resolve competing interpretations into clear conclusions.
Run regular team data reviews, distinguish biological effects from technical or process effects, and identify experiments that will resolve open questions.
Establish and uphold standards for experimental design, controls, documentation, reproducibility, and scientific decision-making.
Facilitate productive scientific disagreement and reach timely conclusions without suppressing dissent.
Lead scientific work for external partner programs, from experimental design through data delivery.
Remain engaged at the bench, personally addressing difficult experiments and troubleshooting.
Build biological systems from first principles, develop models into characterized assays, and deepen existing models.
Own development and maturation of biological assays and workflows for execution on the Parallel Bio platform.
Translate early R&D assays into robust, repeatable, scalable experimental processes.
Develop and execute characterization and optimization strategies for complex organoid and cell-based assays.
Identify critical assay and process parameters and determine how they affect biological outputs.
Design experiments to establish operating ranges, robustness, and sources of variability.
Lead structured, hypothesis-driven troubleshooting of complex biological and process failures.
Define and build frameworks for transferring assays and biological processes from R&D into development and routine Technical Operations.
Set entry and exit criteria for assay maturation and technology transfer.
Establish objective platform-readiness acceptance criteria, including controls, expected ranges, reproducibility requirements, and system suitability.
Ensure transferred assays have adequate documentation, reference data, controls, and scientific understanding for reliable execution.
Partner with Technical Operations so trained operators can execute new processes reproducibly, rather than relying on their original developers.
Lead or support comparability studies when assays, instruments, workflows, reagents, software, or biological inputs change.
Develop strategies to scale biological workflows from small exploratory experiments to higher-throughput platform processes.
Understand and reduce variability associated with operators, instruments, automation, reagents, donors, biological materials, and environmental conditions.
Establish process controls and monitoring strategies for complex biological workflows.
Partner with automation and software teams to translate manual workflows into automated, observable, reproducible platform processes.
Identify where automation, instrumentation, software, or process controls would materially improve scientific performance.
Build processes that balance scientific rigor with throughput, cost, cycle time, and operational complexity.
Partner with R&D to design new assays for eventual scale and platform implementation and prepare them for technology transfer.
Partner with Technical Operations to establish reliable processes for external project execution.
Work with Platform Software, automation, hardware, and data teams to translate biological requirements into platform capabilities.
Contribute to platform roadmap decisions by identifying scientific and process-development capabilities needed for future programs.
Support external pharmaceutical programs by ensuring platform processes are scientifically defensible, reproducible, and appropriate to the questions being asked.
Set acceptance criteria for core organoid workflows, build supporting reference data and controls, establish a recurring scientific review forum, align teams on ownership and decision rights, and drive characterization experiments against priority gaps.