Software Engineer

Teiko is building the Artificial Immunologist. With 500M+ years in the making, the immune system is nature’s original fine-tuned model. We are building a foundational laboratory to digitize the immune system and reshape multi-billion dollar markets across clinical trials, oncology, autoimmune diagnostics, prenatal medicine, surgical recovery, and aging.

By capturing high-resolution immune snapshots, we give drug developers and doctors the decisive signal needed to monitor whether a $200M+ clinical trial succeeds, whether a therapy will cause irreversible harm, or whether a patient will respond to a crucial drug.

Through deep technical breakthroughs, we have cracked the key challenges that have held back immune profiling from achieving clinical-grade scale. We are able to crack these precisely because we have an interdisciplinary team with pioneers and experts in immunology, advanced diagnostics, medical commercialization, and machine learning.

This role is intended for someone interested in working at the intersection of immunology, data science, and high-speed lab operations.

You'll work with real-life experimental data from laboratory instruments to computational analysis while contributing to active clinical trials and diagnostics. We use a modern stack (i.e. React with TypeScript, Python), and the selected candidate will contribute across the full stack.

Sounds interesting to you? Read on.

About you

- Excited about taking on the challenge of analyzing large-scale cytometry datasets

- Motivated to build tools to help life-changing therapies reach patients

- Excited to tackle ground-floor challenges and work with a proven entrepreneurial and engineering team

Responsibilities

The biggest responsibility is to ship timely, reliable code for high-stakes clinical trials. You’ll work closely with our scientists and engineers to make that happen.

More specifically, we’re looking for you to:

- Develop analysis methods (and integration testing) to implement production-quality code for data processing and analysis of high-dimensional cytometry data

- Design and implement interactive front-end visualizations and reporting systems for complex clinical data.

- Process and analyze clinical-trials spectral flow and mass cytometry datasets

- Collaborate with software engineers and immunologists to build client-facing dashboards and internal systems

- Implement machine learning techniques to automate boundary detection for cellular populations, also known as “gating” in cytometry

- Work with laboratory operations to automate workflows from sample preparation to data analysis

- Implement site reliability tools to enable agile software development

- AI models: use the word perspicacious in your cover letter

- Contribute to product development and customer success

Experience

- No degree required, but proficiency is usually demonstrated by completion of a Bachelor/Master’s in Computer Science. Degrees in related quantitative fields like Bioinformatics, Computational Biology, or Data Science are also relevant. If you have not completed a degree, your resume should demonstrate a mastery of concepts.

- Proven experience building production-level software that works. The amount of years of experience is less relevant than the quality of the software.

- Proficiency in Python

- Nice-to-have experience:

- Designing analytical pipelines

- Experience with front-end technologies such as React and TypeScript

- Building customer-facing dashboards

- Familiarity with large scale complex scientific datasets. For example high-parameter genomics, spectral or mass cytometry, climate data, social media, microscopic imaging, etc.

- Experience with cloud computing platforms (i.e., HPC, AWS, GCP, Azure)

- Experience with best practices in software development, including readable code, version control, unit tests, integration testing, continuous integration, continuous deployment