Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Oversee the full lifecycle of research data, including quality, governance, metadata, publication, archival, and FAIR compliance. Partner with multidisciplinary researchers, develop documentation and scalable data infrastructure, support knowledge graph and AI/ML integration, and provide training. The role also requires navigating responsible data-sharing decisions involving privacy, safety, sensitivity, and dual-use risks while collaborating with software engineers and leadership.

Support the Head of Open Science by managing initiatives, workflows, documentation, policy implementation, external proposal intake, stakeholder relationships, events, hiring support, and team onboarding. The role coordinates internal and external stakeholders, screens open science opportunities, prepares leadership materials, tracks decisions, and improves operational processes. It requires strong project management, communication, discretion, and familiarity with open science ecosystems.

Design control-system requirements and architecture for a DNA-origami electrostatic actuator-sensor system. Define sensor and actuator constraints, review FET and drive-stack designs, specify experimental data capture for system identification and machine learning, and develop a closed-loop control, simulation, and estimation plan. Provide a documented handoff to the incoming Controls engineer while advising physics and wet-lab teams on a fractional contract basis.

Software Engineering Intern contributing to large-scale distributed simulation infrastructure. Responsibilities include developing networking and orchestration systems, supporting biological and 3D physics simulations, improving throughput and reliability, debugging performance bottlenecks, and building visualization and developer tools. The intern will collaborate with researchers and engineers on systems programming, distributed computing, and scientific infrastructure projects.

Lead research to develop post-training reinforcement learning methods that convert high-throughput biological measurements into rewards for generative biological language models. Architect and run large-scale model training, work closely with experimental teams to align measurements and modeling, and iterate rapidly to publish new methods and models.

Design and build precision experimental hardware end-to-end, spanning mechanical design, fabrication, electronics, and optics. Lead technical direction, run and equip the prototyping facility, mentor and hire engineers, and collaborate closely with scientists to iterate toward reliable instruments.

Lead design and implementation of low-latency, multi-modal neuroscience research systems: instrument control, data acquisition, high-throughput pipelines, experiment UIs, and cloud infrastructure. Define technical roadmap, mentor engineers, and ensure production reliability and performance for large-scale neural data workflows.

Build and maintain The Stacks web platform: back-end services, front-end interfaces, data models, APIs, cloud infrastructure, CI/CD, testing, and open-source components. Collaborate across teams, iterate rapidly, support post-launch improvements, and ensure availability and observability.

Design and validate an electrostatic drive and field-effect position sensor for a nanoscale DNA-origami actuator; define device stack and direct cleanroom fabrication; perform electrical and force/displacement characterization (including AFM); ensure low-noise measurement toolchain and collaborate with molecular-design and controls teams for closed-loop operation.

Design and build custom precision optical systems (large field-of-view, high-speed two-photon imaging and photostimulation), develop a miniature two-photon microscope for freely moving animals, and build electronics, control hardware, and software to integrate optics with data acquisition. Own instruments end-to-end and iterate designs with scientists and collaborators.