Seeking a highly motivated, veteran Software Engineer with a background in diverse areas from embedded devices to full-stack web-development, experience working with multiple technologies, and multidisciplinary projects.

Who we are

CytoTronics is disrupting the traditional drug discovery process. Spinning out from Harvard after a decade of research, our proprietary semiconductor-cell interface can deliver high-dimensional functional assessment of live-cell responses at scale.

CytoTronics is disrupting biology wet-lab workflows with its innovative engineering approach. Leveraging semiconductors, our proprietary microchip consolidates functionalities from incumbent technologies into every well of a microplate. With significant improvements to resolution and parallelism, we enable applications never before possible and give customers the power to scale assays to unprecedented throughputs.

Check us out at www.cytotronics.com

The Role

As a Sr. Software Engineer at CytoTronics, you will be an early hands-on contributor in the architecture, design and implementation of the software stack that enables our users to accelerate discovery of new drugs and therapeutics.

You will work closely with engineering, biology, and data science teams to generate, process, and analyze measurement data of cell assays, as well as the cloud backend that handles the multiple terabytes of data generated by our instruments.

The software team provides support to all activities at CytoTronics, from the embedded software to data analysis tools running in the cloud. As an early member of the software team, you will be a part in shaping the software environment, implementing best practices, and contribute to the overall direction of the software development process.

The work ranges from driving the real-time software and FPGA that captures and processes the high dimensional transient data in hardware, through uploading, processing, and visualizing the data in the cloud. In practice, you will be building a distributed cloud-based environment, supporting an ever-growing suite of data analysis tools, to transform the raw data (e.g., images, videos, time-series measurements) into biologically meaningful insights that are becoming the basis for innovative drug discoveries.

Who you are

· You are a veteran software engineer. You have worked in multiple software environments and thrive in an early startup full of impact and fun engineering problems.

· You have strong software design and architecture skills that match your coding and troubleshooting talent.

· You have a passion for finding the bottlenecks and identifying where help is needed to get software features to the finish line.

· You are a strong communicator who can grasp new concepts and can translate the needs of users from various backgrounds into simple, maintainable software.

· You have a desire and an innate ability to learn new concepts and explore new domains of knowledge.

· You have the curiosity to tinker with the architecture, identify where to be proactive, develop creative solutions, and improvements that have immediate impact.

· You thrive in a generalist software role, working with the hardware in one sprint, building data-analysis pipelines in the next.

· You are an engineer who can take ownership of large features while closely collaborating with other stakeholders, taking care in planning and testing for reliability and pushing for production.

· You are a polyglot and a user of multiple programming languages and technologies and you are an expert in at least 3 of:

o Python (our primary language)

o Jupyter Notebooks

o TypeScript or JavaScript

o Data acquisition instruments

· You are comfortable contributing to and being a part of DevOps activities and you have a knack for continuously improving the CI/CD process.

Nice To Have

· Signal / Image Processing, Scientific Data Analysis, Bioinformatics

· Cloud integration (AWS preferred), Distributed Systems

· Software for scientific / analytical / imaging devices

· Full-Stack modern end-user web stacks (Python / React preferred)

· Cloud infrastructure DevOps, Docker, Kubernetes, Terraform, etc.

· Embedded Linux, Yocto