Software Engineer II, Pipelines and Workflows
What if you could join a rapidly growing company and play a critical role in bringing new medicines to patients through looking at and treating disease in a revolutionary way.
Founded by Flagship Pioneering, Cellarity is the first company developing medicines through an understanding of cell behaviors. The company’s broad platform harnesses single-cell technologies and machine learning to digitize and quantify cellular behaviors, unravel the network dynamics that govern those behaviors, and generate medicines that can direct them. Cellarity is using its platform to design medicines targeting the full cellular and molecular complexity of disease, enabling a quantum leap in the success rate and speed of drug discovery, design and development. For additional information, visit www.Cellarity.com.
- Be a part of a fast-growing team building out the bioinformatics and machine learning workflows to support a groundbreaking platform driving a new approach to drug discovery.
- Work side by side in a cross functional team of computational biologists and wet lab scientists to define requirements, design and develop automated data processing solutions.
- Monitor and maintain workflows for quality and consistency.
Key Responsibilities Include:
- Work with lab scientists, data scientists, and software engineers within Cellarity to define project requirements for bioinformatics and downstream analysis.
- Design, implement, deploy and maintain production-quality code with unit and integration tests as appropriate.
- Communicate requirements and coordinate work with teams configuring external systems such as our ELN and LIMS.
- Write and maintain documentation of design decisions and code.
- 4+ years experience developing bioinformatics workflows in industry, or in academia with strong code quality standards. (M.S./PhD in Bioinformatics, Computer Science or related field)
- Experience integrating bioinformatics workflows into computational biology and machine learning analysis.
- Ability to communicate and work effectively with internal software and data science teams, external IT contractors and members of other functional teams such biology and chemistry.
- Commitment to building an inclusive team culture that supports and values contributions from all members, regardless of race, gender, background, etc.
- Curiosity to learn about new areas of science and biotechnology.