Jobs at Biohub

Lead and coordinate multidisciplinary imaging science and technology programs, develop and execute project plans, manage technical dependencies, track metrics and progress, communicate with stakeholders, mitigate risks, and document outcomes and best practices to deliver complex AIxBio and imaging initiatives aligned with the strategic roadmap.

Design and evaluate imaging data representations and tokenization strategies for biological AI models. Coordinate across experimental, data science, engineering, and research teams to prioritize data acquisition, define quality criteria, and combine heterogeneous modalities into robust training frameworks that improve model performance and scientific interpretability.

Build and scale frontier AI systems for biology: design model architectures, run large-scale pretraining on GPU clusters, develop RL/reward modeling and multi-agent systems, create evaluation frameworks tied to biological outcomes, and publish/open-source research.

Develop and maintain analysis workflows and visualization tools for spatiotemporal multi-omics datasets; integrate proteomics and metabolomics; apply machine learning approaches; collaborate with experimental teams and contribute to publications and open-source software.

Develop and scale frontier AI systems for biology, including foundation models, pre-training pipelines, RL and multi-agent systems, evaluation frameworks, and community-facing publications and open-source releases to accelerate scientific discovery.

Develop and scale deep learning foundation models and systems for biology. Design model architectures and pre-training pipelines, build post-training discovery systems (RL, reward modeling, reasoning, multi-agent orchestration), create evaluation frameworks tied to biological outcomes, and publish/open-source results while collaborating with scientists worldwide.

Manage daily wet-lab operations, inventory, equipment maintenance, and incident response. Develop and enforce safety protocols, SOPs, chemical and biohazard waste handling in coordination with EH&S. Identify operational risks, propose process improvements, support long-term lab planning, and provide general lab management support to scientists and platform leaders.

Lead design and operation of hybrid HPC-AI infrastructure supporting large-scale GPU training, low-latency inference, and data-heavy pipelines. Architect and optimize on-prem and cloud GPU resources, integrate MLOps and deployment pipelines, implement advanced scheduling (Slurm, Kubernetes, SUNK), manage storage and networking, support researchers on performance tuning, and drive adoption of AI tooling across teams.

Operate and scale multi-site multi-GPU clusters running Slurm on Kubernetes: ensure reliability and observability, debug storage/network/GPU failures, automate capacity and lifecycle management, drive configuration-as-code, partner with researchers and vendors, and reduce incident MTTR while enabling multi-thousand GPU training runs.

Perform biochemical and biophysical assays to characterize AI-designed molecules, design and construct plasmids, develop and run protein and cell-based assays, document and analyze results, and collaborate with AI researchers to translate experimental data into research insights.

Design and build petabyte-scale data pipelines and platform tooling to ingest, transform, catalog, and deliver heterogeneous biological datasets for AI research. Improve reliability, observability, and automation (agent-based curation/QA) while collaborating with AI researchers and scientists.

Lead AI safety research for biological applications: design safety evaluations, assess emerging capabilities, partner with scientists to build robust safeguards, inform policy, and communicate results to internal and external stakeholders.

Develop and scale frontier AI systems for biology, including foundation models, RL and multi-agent systems. Design model architectures, pre-training and post-training discovery pipelines, evaluation frameworks, and publish/open-source research with scientific collaborators.