Optical Engineer, Advanced Light Sheet Microscopy

Biohub•San Francisco, CA

1d•Hybrid

About The Position

Biohub is seeking an Optical Engineer, Advanced Light Sheet Microscopy with strong hands-on engineering skills, experience building and integrating scientific instrumentation, ideally lightsheet microscopes, and solid programming expertise for hardware control and automation. The successful candidate will combine practical advanced optical design and system-building experience with the ability to develop and maintain robust control software for advanced light-sheet microscopes. This role involves collaborating with scientists, bioengineers, computer scientists, and biologists to co-design and build imaging systems, optimize instruments, and design automation for time-lapse imaging of live specimens. The goal is to elucidate the complex collective dynamics of self-organizing cellular systems across scales in health and disease using state-of-the-art light-sheet microscopes to visualize zebrafish embryonic development.

Requirements

Master of Science, or PhD degree in Optics, Biomedical Engineering, Electrical Engineering, Mechanical Engineering, Robotics, or a related field.
Strong practical engineering skills with demonstrated experience designing, prototyping, and iterating hardware control systems (at least 5 years).
Solid working knowledge of electronics and embedded systems, including microcontrollers, DACs/ADCs, and basic PCB design (at least 4 years).
Experience with CAD design (e.g., SolidWorks, OnShape, or similar) and rapid prototyping methods such as 3D printing, machining, laser cutting (at least 3 years)
Strong programming experience in Python; Experience with C/C++/Rust desired (at least 5 years).
Proven experience developing hardware control scripts and integrating third-party devices.
Proven ability to troubleshoot complex mechanical, electrical, and software systems in experimental or research environments.
Strong communication skills and a collaborative mindset; ability to work effectively within a multidisciplinary team.

Nice To Haves

Any tangible ‘extra-curricular’ evidence of exceptional abilities in the disciplines above, such as hobby projects in robotics, electronics, optics, DIY instrumentation, open-source hardware/software, are extremely welcome.
Knowledge and experience in light-sheet microscopy or other similar precision optical instruments are highly desirable.
Experience or interest in integrating Adaptive Optics (AO) components (e.g., deformable mirrors)
Experience with feedback control systems, sensors, and real-time automation.
Experience designing or integrating thermal control, microfluidic, perfusion, or environmental control systems.
Experience and deep understanding of low-level coding in C and C++.
Familiarity with high-performance computing concepts (multi-threading, GPU acceleration, parallel processing) for image processing or data-intensive applications.
Familiarity with Linux-based systems and device driver configuration.
Familiarity with optical metrology, such as PSF characterization.
Experience working in a biological or life sciences research environment.

Responsibilities

Design, prototype, implement, and optimise custom subsystems for light-sheet microscopes and other advanced imaging platforms.
Integrate mechanical, thermal, fluidic, optical, and electronic components into cohesive, reliable experimental systems.
Develop modular hardware control software in Python (and occasionally C/C++), interfacing with cameras, stages, lasers, sensors, and other instrumentation components.
Design and implement automated or “smart” imaging protocols incorporating feedback loops (e.g., sensor-driven control, adaptive imaging strategies, and real-time decision-making).
Collaborate with scientists, bioengineers, computer scientists, and biologists to implement new features and capabilities, including hardware interfaces, acquisition modes, graphical user interfaces, smart automation, high-performance data visualization, and scalable data storage pipelines.
Contribute to data acquisition workflows capable of handling large-scale imaging datasets, including performance optimization, structured data saving, and integration with downstream analysis pipelines.
Document system architectures, mechanical designs, schematics, and assembly procedures to ensure reproducibility, maintainability, and scalability.