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 engineers to build the environment that powers the next era of life-saving treatments for patients. Our full-stack engineers will 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 a mission-driven individual that is capable of rapidly bringing ideas from 0 to 1 and eager to apply software engineering skills to life-saving cures.
If you enjoy building solutions like the ones below, we’d love to hear from you!
- Designing cloud infrastructure to serve billions of predictions for machine learning models via Kubernetes on Google Cloud Platform and Amazon Web Services
- Building scalable machine learning infrastructure so that ML engineers can train thousands of models at scale, visualize performance, and analyze results
- Designing and developing internal web-based tools using the latest web technologies to enable computational chemists to explore molecular properties
- Connecting Docker-based microservices and serverless scripts to enable automated dataset ingestion pipelines that speed up the pace of model development and serving.
- Architecting and building cloud-based data lakes along with 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:
- Python development: Strong 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.
- Web development experience - 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
- We are ideally looking for folks with 3+ years of industry experience, but we are open to strong applicants of any background level.
- 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.