Senior Software Engineer, Full Stack
Cambridge, MA /
At Reverie Labs, we’re building a pharmaceutical company from the ground up using computation—we’re a biotech company that looks and feels like a tech company.
We’re looking for a Senior Software Engineer to help us build the environment that powers the next era of life-saving treatments for patients. Our software engineers work side-by-side with our machine learning engineers, computational chemists, and medicinal chemists to achieve drug discovery objectives, spanning our entire tech stack. We are looking for mission-driven individuals that are capable of rapidly bringing ideas from 0 to 1 and eager to apply software engineering skills to life-saving cures.
If you enjoy challenges like the ones below, we’d love to hear from you!
- Architecting a Django REST-driven internal application development ecosystem that supports multiple drug development programs.
- Using web frameworks (Django, React, etc) to architect intuitive user interfaces for non-technical users to interact with machine learning software.
- Building performant software for billion-scale molecular analyses alongside machine learning engineers.
- Owning and leading code deployments, testing, and maintenance.
- Designing and implementing front-end interfaces that enable our in-house chemistry team to interface with software.
- Connecting Docker-based microservices and serverless scripts to enable automated dataset ingestion pipelines that speed up the pace of model development and serving.
- Leading a team of software engineers in adopting industry best-practices for web technologies.
- Designing data APIs to power machine learning models, visualization tools, and chemistry software.
We don’t have a hard set of background requirements, but generally we most value skills and experience in the following areas:
- We are ideally looking for folks with 5+ years of industry experience.
- Python development: Experience building production systems in Python, especially in a microservices or serverless environment.
- Containerization: Experience in using Docker and Kubernetes to containerize and launch microservices. ML-specific experience not required or expected.
- Ability to rapidly prototype and launch internal-facing web applications using frameworks like Django.
- ML in Production: Knowledge of best-practices for building automated data ingestion and model deployment pipelines
- Most importantly, an eagerness to learn new skills, wear many hats, and collaborate closely with a growing team of people.
Finally, we base our employment decisions entirely on business needs, job requirements, and qualifications—we do not discriminate based on race, gender, religion, health, parental status, personal beliefs, veteran status, age, or any other status. We have zero tolerance for any kind of discrimination, and we are looking for candidates who share those values. Applications from women and members of underrepresented minority groups are particularly welcomed.