Senior/Staff Software Engineer - Full Stack

The Role

Senior/Staff Software Engineer - Full Stack. Dyno is seeking an experienced full stack engineer to lead development of new internal and external products for designing genetic sequences that strengthen Dyno’s position.

How You Will Contribute

As a Senior/Staff Software Engineer - Full Stack on the ML Products Team, you will be a core contributor to new products that will amplify scientists’ capabilities and impact on patients. You’ll build across the stack, ranging from database interfaces, scalable backend web services, frontend development, and incorporating ML models and LLMs into products. 

Responsibilities: 

• Lead end-to-end development of new products for genetic sequence design within the ML Products team.
• Iterating on ideas and prototypes and then prioritizing the path to an MVP.
• Develop and disseminate best practices for repeatable and scalable end to end product development.
• Collaborate with team members ranging from engineers, computational biologists, ML researchers, and biologists to come up with and build great products.
• Mentor and teach other engineers on the team.

Who you are 

• Trusted partner
• Team oriented
• Thoughtful & detail oriented 
• Work with a sense of urgency
• Excited about building amazing product experiences that wow scientists
• Appreciation for opportunities at the intersections of data science and biology
• Comfortable with rapid iteration and shifting priorities

Basic qualifications

• Strong programming and system design fundamentals with 4+ years of experience with full stack development.
• Developing frontend applications using modern frameworks such as React (or other comparable frameworks such as Vue.js, Svelte, etc.).
• Backend system design & development from DB to API.
• Experience working cross-team to communicate with both technical and business stakeholders as well as customers.

Preferred qualifications

• Experience with Python backend development (examples include: Django, FastAPI, Flask, etc.).
• Demonstrated examples of applying product taste.
• Excitement about (but not necessarily experience with) building products that let scientists do more, faster.
• Experience building on top of ML models and/or LLMs.
• Have built products in the 0-1 stage.
• Even limited experience managing cloud deployments and environments.
• Excited to learn about bio/gene therapy (no experience necessary).