Senior Scientific Platform Engineer
New
V
VivoSenseDigital Health
US REMOTE (AZ, CA, CO, FL, GA, MA, MD, NC, NJ, NH, NV, OH, OR, PA, TN, TX)Full-TimeSenior
Salary$130,000 - $160,000 annual USD (DOE and Location)
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonSoftware ArchitectureRESTful APIs
Requirements
- Master's or Ph.D. degree in Computer Science, Software Engineering, Biomedical Engineering, Data Science, Bioinformatics, or related technical field.
- 5+ years of experience developing software applications, analytics platforms, scientific computing solutions, or data processing systems.
- Strong proficiency in Python and experience building production-grade backend services, APIs, and data processing pipelines.
- Experience developing cloud-native applications on AWS, including modern distributed, serverless, or event-driven architectures.
- Ability to translate scientific methods and analytical workflows into scalable, maintainable, and production-ready software solutions.
- Experience integrating analytical, scientific, or data-driven workflows into enterprise software platforms.
- Experience using AI-assisted development tools for code modernization and productivity improvement.
- Strong understanding of software architecture, testing, debugging, and software development best practices.
- Strong analytical, problem-solving, and technical documentation skills.
Responsibilities
- Develop and maintain software components, data processing workflows, reporting solutions, and platform services that support study execution and customer deliverables.
- Support the commercialization and operationalization of scientific innovations by transforming research outputs into robust software solutions used in clinical studies and customer-facing deliverables.
- Design and implement integrations for new sensors, data sources, and platform capabilities.
- Create and maintain technical designs, implementation specifications, validation documentation, and operational procedures.
- Support verification, validation, testing, troubleshooting, and release activities to ensure high-quality and reliable platform functionality.
- Partner with Engineering teams to design, implement, test, and deploy scientific workflows and analytical capabilities.
- Identify opportunities to improve platform scalability, maintainability, automation, and operational efficiency.
- Collaborate with cross-functional teams to define requirements, prioritize work, and drive successful project delivery.
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