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 Infrastructure Engineers to expand our data platform and enable high-throughput modeling and inference workflows that will accelerate our mission of designing life-saving treatments for patients. Our infrastructure engineers will work side-by-side with our machine learning engineers, computational chemists, and medicinal chemists to achieve drug discovery objectives. We are looking for a mission-driven individual that is capable of rapidly bringing ideas from 0 to 1 and is eager to apply infrastructure development skills to developing medicines.
Do the following problems sound like a fun challenge to you? If so, 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 data pipelines to integrate with in-house and third-party data sources that then power machine learning workflows
- Architecting and building cloud-based data lakes along with APIs to power machine learning models, visualization tools, and chemistry software.
- Writing continuous integration and delivery tools to build new Docker containers, deploy updated models, and distribute code in response to Git hooks or other web events.
- Connecting Docker-based microservices and serverless scripts to enable automated dataset ingestion pipelines that speed up the pace of model development and serving.
We don’t have a hard set of background requirements, but generally we most value skills and experience in the following areas:
- Data Engineering: Knowledge of data pipelining and storage tools to enable large-scale data processing workflows.
- Containerization: Experience in using Docker and Kubernetes to containerize and launch microservices. ML-specific experience not required.
- Python development: Strong experience building production systems in Python, especially in a microservices or serverless environment.
- 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.
About Reverie Labs
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 focused on using machine learning and computational scale to solve challenging problems in cancer drug discovery.
We foster a scrappy, rapid-prototyping mindset to our work. Engineers are encouraged to take time to try bold ideas and seek feedback early and often to improve the quality of the outcome. We don't like reinventing the wheel - drug discovery is already hard enough. Engineers are encouraged to use and contribute to open-source software, allowing us to quickly build solutions and focus on advancing the science of drug discovery.
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