Jobs at Allen Institute

Lead and optimize the organization’s contracts program, managing the full contract lifecycle and administering the CLM platform. Draft and negotiate research, services, consulting, and commercial agreements; maintain templates, playbooks, workflows, documentation, and service standards; implement technology and AI process improvements; collaborate with Legal on risk strategies; and supervise contract specialists supporting internal and external stakeholders.

Build and maintain machine learning training, evaluation, data access, and model infrastructure for biological research. Responsibilities include designing large-scale data storage and versioning systems, maintaining a model zoo, supporting lab-in-the-loop training, making build-versus-buy decisions, and collaborating with AI scientists to develop novel models.

Develop, maintain, and deploy sustainable scientific software for large-scale neurophysiology data processing and analysis. Collaborate with computational scientists, implement testing and software development best practices, manage cloud and on-premise services, build end-to-end pipeline testing infrastructure, and contribute to open-source neuroscience analysis and visualization tools. Mentor colleagues and support reproducible data workflows in an Agile environment.

Invent and evaluate novel AI/ML methods for large-scale biological data. Design experiments, benchmarks, and reusable modeling frameworks; collaborate with scientists and engineers; publish and share methods to advance scientific discovery.

Build, deploy, and maintain cloud and on-premises infrastructure for high-throughput data pipelines. Define Linux configuration as code (Ansible), manage Terraform-based AWS infrastructure, support CI/CD, databases, logging and metrics, troubleshoot production/staging issues, and participate in on-hours support rotations.

Manage a large Linux-based scientific computing environment, including servers, workstations, storage, cloud infrastructure, patching, cybersecurity agents, monitoring, lifecycle management, and performance scaling. Design and deploy infrastructure services, automate operations with shell or Python, develop system standards, and support highly available services. The role includes rotating evening and weekend on-call coverage, occasional additional hours, and local travel to data centers or other institute locations.

Designs and executes high-throughput barcoded connectomics and transcriptomics experiments, analyzes large-scale datasets, maintains and improves data production/processing software, coordinates data acquisition and deposition, publishes results, and collaborates across teams and external partners to reveal brain wiring principles.

Design and perform scalable synapse-type specific proteomics experiments, develop workflows for synapse isolation and proteomic analysis, analyze and integrate large-scale proteomic and multimodal data, coordinate with internal teams and core facilities, manage data acquisition/storage, and publish and present findings while executing collaborative projects.

Support large-scale synapse and neuronal-population proteomics by performing mouse tissue dissections, synapse isolation, proteomic sample preparation, histology, fluorescence imaging and sorting, and related molecular biology and viral vector workflows. Maintain lab records, follow SOPs and regulatory requirements, troubleshoot and optimize protocols, coordinate with cores, and present results within a collaborative team environment.

Lead institute-wide data governance, metadata standards, and lifecycle management for large multimodal biological datasets. Own data stewardship, cataloging, and compliance (NIST/HIPAA), drive adoption of standards, advise scientific and technical leaders, and lead cross-functional initiatives to improve discoverability, reuse, and long-term data sustainability.

Lead external scientific communication and community engagement for the Immunology accelerator. Translate complex immunology into clear narratives, social content, figures, and tutorials. Create visual storytelling for leadership and publications, develop documentation and onboarding for data/tools, coordinate seminars and training, and work closely with scientific leadership and Communications to expand reach, adoption, and public understanding of Institute discoveries.

Lead scientific computing strategy for Neural Dynamics: scale petabyte data platforms, build performant data pipelines, apply state-of-the-art ML and foundation models to multimodal biological data, establish engineering best practices, form strategic partnerships, and manage engineering teams to enable open-science discovery in neuroscience.

Serve as strategic legal advisor to executive leadership and the Board, lead the in-house legal team, and oversee governance, compliance, risk management, and enterprise legal operations. Advise on nonprofit and tax-exempt law, AI governance, IP and technology transactions, export controls, sponsored research, data privacy, cybersecurity, employment, and federal contracting. Negotiate complex agreements, manage outside counsel, and build scalable legal processes to enable scientific innovation and institutional mission.

Lead and scale image processing for large-scale electron microscopy datasets, oversee 2D stitching and 3D alignment pipelines, analyze connectomics data with multidisciplinary teams, publish results, and mentor/coordinate team activities across institutions.

Architect, build, and operate cloud and on‑prem AI/ML training and inference platforms (including federated learning). Partner with scientists and external collaborators, benchmark and optimize ML infrastructure, ensure security/compliance and cost effectiveness, mentor engineers, and represent the Institute in vendor and cross‑institutional technical engagements.

Design, train, and deploy large-scale AI/ML models for multimodal biological data; build research-grade ML infrastructure and data pipelines; collaborate with scientists and engineers; establish best practices and community standards; publish and open-source methods and code.

Lead analysis of large-scale, multi-region neural recordings and behavioral data. Build reproducible pipelines, apply statistical and quantitative models, collaborate with experimentalists, present and publish results, and engage in theory development and journal club.

Design, develop, and apply molecular and proteomic technologies (e.g., spatial and droplet-based NGS) to study immune mechanisms. Perform and analyze in vitro and ex vivo immunology experiments using cell lines, primary cells, tissues, and genetic models. Develop cellular engineering and screening approaches, collaborate with teams to execute projects on timeline, and synthesize data from molecular, cellular, and proteomic platforms.

Design and implement modern ML and Bayesian algorithms to model multimodal disease progression (omics, pathology, imaging, genetics, clinical data), harmonize cohorts, develop causal and generative models, collaborate across teams, and publish results.