Company Overview: Terray Therapeutics is a venture-backed biotechnology company led by pioneers and long-time leaders in artificial intelligence, synthetic chemistry, automation, and nanotechnology. We’re generating chemical data purpose-built to propel drug discovery into the information age — and we’re doing it on a larger scale and faster than has ever before been possible.
Our closed loop system generates precise chemical datasets at unrivaled scale that work seamlessly with AI to systematically map biochemical interactions between small molecules and causes of disease. Iterative cycles of virtual molecular design and experimentation power AI and machine learning models, which in turn guide the next cycle of design. With a chemistry engine that measures billions of interactions daily and becomes increasingly precise with every cycle, we can answer an unprecedented array of questions — deriving insights that enable us to predictably create drugs for patients in need.
Position Summary: Terray is currently seeking a motivated, creative, and experienced software engineer. As an integral member of our Computational and Data Sciences (CDS) team, the candidate will be responsible for developing, deploying, and maintaining the data pipelines, workflows, and tooling that power our wet-lab and computational discovery platforms.
The core responsibilities of this position are:
- Build, maintain, and improve statistical data pipelines for our computational platform, including hit identification done on our platform, assignment and progression of compounds through off-platform biochemical and cellular assays, and other downstream processes to support pipeline progression
- Design, develop, and deploy database schemas, software tools, and algorithms that will enable and improve our computational and wet lab workflows to support our drug development pipelines
Experience and Qualifications: Part of Terray’s success is nurtured by a hands-on work environment where everyone is accountable, vested in a vision of excellence, and actively taking part in the success of the business. Terray supports a positive work environment where employees can feel engaged, recognized and empowered to be creative.
Required Qualifications:
- BS/MS/PhD in Computer Science or related field
- Highly proficient in Python and the PyData stack (numpy, pandas, scipy, scikit-learn, etc.)
- Proficiency in Linux environment, experience with database languages
- Familiar with AWS cloud resources and services like Batch
- Experience with designing and building out database schemas
- Demonstrated ability to write high-quality, production-ready code
- Understanding of CI/CD and Agile software engineering practices and experience with container build and deployment systems like Docker
- Knowledge of coding best practices, including standards, reviews, version control, and unit testing
Preferred Qualifications:
- Experience with turning statistical and/or machine learning algorithms into performant production code
- Familiarity with a frontend framework (ex: React, Vue) and prototyping tools (Streamlit)
- Familiarity with wet-lab procedures and/or has experience interacting with wet-lab scientists to scope and build software tools
- Natural leader with ability to guide system design and effective documentation
Compensation Details: $140,000 - $216,000 (annually) depending on seniority; participation in the Company's option plan; 3% retirement safe harbor contribution; fully-paid medical, dental, vision, life and disability benefits.
Top Skills
What We Do
Chemistry is the key to drug discovery, but chemical data is stuck in the twentieth century. We’re generating precise chemical datasets purpose-built to propel drug discovery into the information age — and we’re doing it on a larger scale and faster than has ever before been possible.
Terray Therapeutics is a biotechnology company led by pioneers and long-time leaders in artificial intelligence, synthetic (medicinal) chemistry, biology and preclinical development, automation, and nanotechnology. Chemical datasets generated using our novel ultra-dense microarray technology work seamlessly with our integrated machine learning and computational platform to systematically map biochemical interactions between small molecules and causes of disease. Iterative cycles of virtual molecular design and experimentation power AI and machine learning models, which in turn guide the next cycle of design.
With a chemistry engine that measures billions of interactions daily and becomes increasingly precise with every cycle, we can answer an unprecedented array of questions — deriving insights that enable us to predictably create drugs for patients in need.
