Cephla is building the critical imaging infrastructure for modern biology and drug discovery. Our open and programmable automated microscopes and integrated solutions around them take down barriers to high-end imaging and methods adoption — they are already powering research and large-scale data production at leading academic labs, biotech startups, and pharma. In parallel, our Octopi brings AI-enabled microscopy to diagnostics, starting with malaria.
We're a small team of scientists and engineers, mission-driven and deeply invested in our users' success as the experiments running on our instruments are often critical to research that will advance science and can impact human health. In this role, besides working closely with the founders and the rest of our team, you will directly collaborate with our partners and users across research institutes, pharma, and techbio startups, with applications spanning from basic research to precision medicine. Through our upcoming collaborations with leading cancer centers, your work could directly impact patient care.
Responsibilities
You will work across research and engineering, owning projects from idea to production, with aspects including:
- Smart acquisition — building or deploying ML and computer vision models that decide what to image, when, and how (focus, ROI selection, channel switching, rare-event detection)
- Online image analysis — segmentation, detection, classification, and QC running during acquisition, not after
- Closed-loop experiments — building the adaptive control layer on top of our existing imaging, fluidics, and robotics integrations, and the abstractions that let users (and increasingly, agents) define and run protocols
- Deployment — shipping what you build for robust production use on our users' instruments and automation workcells
Depending on your interests and what we need, your work may also stretch into:
- Foundation-model and self-supervised approaches for microscopy data
- Software infrastructure for microscope farms and large-scale automation — running, monitoring, and learning from many instruments at once
- Data infrastructure — improving how microscopy datasets flow from instruments to storage to training pipelines
- Exploratory work on computational imaging and new acquisition modalities
Required qualifications
- Currently pursuing or recently completed a degree in Computer Science, Electrical Engineering, Bioengineering, Physics, Applied Math, or a related field
- Strong software engineering fundamentals
- Demonstrated hands-on building experience — open-source contributions, personal projects, research, prior internships, anything where you've actually shipped working software or models
- Excellent communication (written and verbal)
Preferred qualifications
- Prior research or internship experience with a concrete output — ideally a first-author publication, ML/computer vision systems/software shipped to production, or both
- Experience with image analysis for microscopy or biological data
- Experience working with hardware systems
Additional Requirements and Competencies
- Resourceful, flexible and adaptable. You're happy to take on whatever the project needs
- Comfortable with ambiguity. You find that having to define the problem is exciting rather than frustrating
- You move fast and you deliver. Quick experimentation and follow-through matter — a model running reliably on a real instrument beats a clever idea sitting in a notebook
- You can work closely with the people you build for — scientists, cancer researchers, and clinicians — and find that energizing rather than distracting
Who will love this job (and who we're looking for)
- You are after an outsized impact on accelerating science and improving patient care
- You want to work where the field is being defined, not where it's already settled
- You want a role with very high autonomy
- You enjoy working with hardware/robotic systems
Expected Compensation
$4,000 – $5,500 per month.