Software Engineer, LLM & Automation
BasisPart Time
Mid-level (3 to 4 years)
The ideal candidate has over 5 years of experience developing distributed systems for large dataset collection and processing, with proficiency in full-stack development using Node.js, Typescript, or Python. Experience with web front-end frameworks like React, container technologies such as Docker, and cloud infrastructure providers (AWS, Azure, GCP) is required. Familiarity with writing maintainable unit and integration tests, strong application debugging skills, excellent communication and technical writing abilities, and experience in Life Sciences or scientific data are also necessary.
The Software Engineer will join the Tetra engineering team to build platforms, SDKs, and tools using various languages and software stacks. Responsibilities include self-starting and making progress in ambiguous situations, designing and developing efficient solutions for automating lab data flows, and creating tools for others to do the same. The role involves addressing resiliency, scale, and high availability requirements, delivering a high-quality product through agile development, and partnering with product management to translate vision into reality. Additionally, the engineer will collaborate with a geographically dispersed team, speak up and represent their position, and remain resilient and open to feedback.
Cloud platform for scientific data management
TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.