We are looking for a experienced software engineer (technical lead) with deep knowledge of cloud infrastructures and data warehousing to join our foundational software team.
At Asimov, machine learning and scalable software systems are core to our product; we engineer living cells by designing and inserting genetic circuits into living organisms. The design of these circuits draws on principles from automated circuit design and numerical optimization.
We care deeply about every engineer’s autonomy, emphasizing quality of engineering over arbitrary deadlines. We have built a cross-functional organization and believe strongly in cross pollination: taking time to learn from our peers.
As our Software technical lead you will have the opportunity to:
- Design and architect the backend for our computer aided genetic circuit pipeline, including the genetic compiler and simulation engine
- Develop our cloud infrastructure, data warehouse, build and deploy system, and machine learning platform. You will drive discussion and decisions on microservices vs monoliths, managed services vs deployed, etc.
- Work on tooling to help improve the efficiencies of our synthetic biologists including data analysis platforms and robotic automation
Beyond technical skills, we are looking for individuals who are:
- solid at communicating architectures internally through clear design documents
- embracing ambiguity and driving for impact
- excited to partner closely with and learn from our synthetic biology team
- interested in helping define the company product, direction and culture
You are a highly skilled technical lead in software engineer with years of experience in industry. You are passionate about joining an early stage startup where autonomy, passion to learn and excitement to engineer biology take precedence over process and ego. If you have a background in genetics or cellular biology, great! If not, you have strong experience with ETL systems, data storage and access, cloud infrastructures, build and deploy systems with a passion to learn the science.