TetraScience

Software Engineer III - Lab Data Automation

United States

Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Lab Data ManagementIndustries

Requirements

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.

Responsibilities

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.

Skills

Software Development
Data Automation
SDK Development
Agile Methodologies
Problem Solving
Resiliency
Scalability
High Availability

TetraScience

Cloud platform for scientific data management

About TetraScience

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.

Boston, MassachusettsHeadquarters
2019Year Founded
$113.8MTotal Funding
SERIES_BCompany Stage
AI & Machine Learning, Biotechnology, HealthcareIndustries
51-200Employees

Benefits

Unlimited PTO
100% company paid health, dental, & vision
Company paid life insurance
401k savings
Company paid disability insurance
Equity program
Flexible work arrangements

Risks

Rapid AI development may outpace TetraScience's integration capabilities, risking obsolescence.
Dependency on partners like Google Cloud and NVIDIA could pose risks if disrupted.
International expansion may expose TetraScience to regulatory and compliance challenges.

Differentiation

TetraScience offers a vendor-neutral, open, cloud-native platform for scientific data management.
The platform integrates with any lab equipment or software, enhancing flexibility and adaptability.
TetraScience's Scientific Data Cloud centralizes and harmonizes data, preparing it for AI/ML applications.

Upsides

Partnerships with NVIDIA and Google Cloud enhance AI-native scientific datasets and capabilities.
Collaboration with Databricks accelerates the Scientific AI revolution in life sciences.
Bayer AG partnership maximizes scientific data value, driving innovation in biopharma.

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