Software Engineer (Jr to Sr Levels)

at  nomic

ABOUT US:

Nomic was founded with the purpose of making biology easier to measure. To do this, we have untangled some of the most difficult problems in protein profiling. Our team is combining DNA nanotechnology, high-dimensional flow cytometry, laboratory automation, and machine learning to develop the world’s highest throughput proteomic platform: the nELISA.
Since spinning out of McGill University, we have partnered with and provided platform access to dozens of drug discovery groups including GSK, 4 of the top 10 pharmas, and leading biotechs. We have recently launched a state of the art manufacturing and protein profiling facility that enables multiplexed measurement of >2.5M samples a year, generating an effective 500M protein assays in the process.
We are building a diverse team of engineers, scientists, and world-changers. We like to break down difficult problems using a first principles approach, often leveraging the latest breakthroughs from across the scientific and technological spectrum to drive our mission forward.
Nomic is headquartered in Montreal, Canada with a satellite research lab in Boston, Massachusetts. The majority of our team is based in Montreal and works in a new, shared office/laboratory space.

Our Software team’s mission is to design, build, and support world class software that empowers all nELISA users with proteomics superpowers, including internal at Nomic. Software is integral to our vision of the future, and every aspect of our company today will depend on improving our software stack. Functionally, our software stack includes (i) an in-house developed full-stack LIMS that underpins inventory, manufacturing, lab operations, and that will continue to drive further lab automation going forward; (ii) data pipelines and associated cloud data infrastructure to monitor, decode, and quantitatively analyze flow cytometry nELISA experiments; and (iii) a customer-facing web portal that enables nELISA users to visualize and analyze their proteomic datasets at scale seamlessly in the browser.
As a Software Engineer, you will be responsible for building all core components of the nELISA software stack, and scaling them as needed, often as a member of cross-functional projects working closely with our broader Engineering, Commercial, and Lab Operations teams. You will also get to build internal tools that create and support data-driven feedback loops for our teammates in R&D, automation, manufacturing, customer success, and bioinformatics. In short, you will get to make substantive changes and build the core components of the software stack that underpins the nELISA’s technological flywheel.

You will therefore get to play a critical, first-hand role in developing core improvements to the LIMS, web portal, and data infrastructure for handling all things nELISA data. In particular, you will:

• Write sub-components of our software stack from scratch, such as database schemas, analysis pipelines and new analysis algorithms, cloud infrastructure and related IaC, full stack web interfaces, machine learning models, and APIs that will be consumed both by our own services, and by customers.
• Develop improved internal tools for our LIMS, and software for our R&D teams, in order to increase operations and R&D velocity in the lab, including developing and implementing an electronic lab notebooks (ELN) plan tailor fit to our profiling and manufacturing lab operations.
• Write modular software that we can use to create efficient analysis pipelines and internal QC tools, making use of existing libraries, open source platforms, and commercial options as best suited to the challenges at hand.
• Build better interfaces to the tools that are available out-of-the-box from our robotic lab automation equipment suppliers, and extend these capabilities going forward so as to enable our lab teams to interface with our software stack as seamlessly as possible.
• Contribute improvements to the codebase that enable us to further scale up our nELISA decoding and analysis pipelines, write test cases, integrate components of the stack with appropriate monitoring and analytics, and set up robust CICD infrastructure when appropriate.
• Deploy and scale our data pipelines for processing flow cytometry data into quantitative protein concentrations. This will be done in close collaboration between our Data Engineering and Software Engineering teams.
• This role will involve substantial communication and teamwork not just within our software engineering team at Nomic, but also with the broader range of internal users of the LIMS, data portal, and data pipeline software, including customers at times.