Software Engineer, Data Infrastructure & Acquisition
SpeechifySalary not specified
Full Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Lab Data ManagementIndustries
Requirements
Candidates should have 8+ years of experience designing and developing distributed systems for large datasets, proficiency in Node.js, Typescript, Docker, and cloud platforms (AWS, Azure, GCP), and a strong understanding of threading, parallelism, concurrency, and networking concepts. Familiarity with writing unit and integration tests, on-premise distributed software support, cross-platform development, debugging, and strong communication skills are also required. A Bachelor's or Master's degree in Computer Science or equivalent is necessary, with Python and Life Sciences experience being advantageous.
Responsibilities
The Senior Software Engineer will join the data acquisition team to build high-performance data management tools for scientific instruments and other data sources. Responsibilities include self-starting and making progress in ambiguous situations, designing and developing efficient data extraction and distribution solutions, addressing resiliency, scale, and high availability requirements, and delivering a high-quality product using agile methodologies. The role also involves partnering with product management to translate vision into reality and collaborating effectively with a geographically dispersed team.
Skills
Data Acquisition
Data Management
Software Development
Agile Methodology
Problem Solving
Scalability
High Availability
Resiliency
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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