Principal Software Engineer - Cambridge - Vizgen Inc.

    Vizgen Inc.
    Vizgen Inc. Cambridge

    1 week ago

    Description
    About Vizgen:
    Vizgen is revolutionizing genomics with cutting-edge technologies that reveal the spatial organization of genes within tissues. By harnessing the power of MERFISH and the MERSCOPE platform, Vizgen enables researchers to explore cellular functions and interactions with unprecedented clarity and resolution. MERFISH (Multiplexed Error-Robust Fluorescence In Situ Hybridization) platform, enables high-resolution mapping of gene expressions within intact tissue samples. Our proprietary solutions enable translational and clinical research groups to explore complex biological systems and diseases at the cellular level, offering transformative insights into biomedical research and drug discovery.
    The Role:
    The Principal Software Engineer for MERSCOPE instrument software will lead the design, development, and deployment of the control systems that power Vizgen's cutting-edge spatial genomics platform. This role focuses on Python-based backend and instrument control software, including deployment automation and release reliability across laboratory instruments in the field. The ideal candidate combines deep software engineering experience with a practical understanding of complex, hardware-integrated systems.
    Responsibilities:
    • Lead development of MERSCOPE instrument software, primarily written in Python, including data acquisition, hardware control, and analysis components.
    • Modernize and improve deployment infrastructure, enabling faster, safer delivery of instrument software updates.
    • Collaborate closely with hardware, wet lab, and field support teams to ensure the software meets the needs of scientists and instrument operators.
    • Define and maintain software architecture, emphasizing reliability, maintainability, and testability.
    • Identify technical debt and lead remediation efforts that directly improve uptime, update cadence, and supportability.
    • Design and enforce CI/CD workflows, versioning strategies, and validation processes appropriate for scientific instruments.
    • Mentor engineers in best practices for Python development, software testing, and deployment automation.
    • Review, approve, and sign off on releases from a technical and operational perspective.
    • Partner with product management to scope and prioritize new instrument features and optimizations.
    Requirements:
    • Proven experience as a Principal Engineer, Tech Lead, or Software Architect in a production-grade scientific or hardware-integrated software system.
    • Expert-level proficiency in Python, including asynchronous programming, packaging, and dependency management.
    • Strong understanding of hexagonal architecture
    • Strong experience with Linux-based development and deployment environments with familiarity working in Windows runtime environment.
    • Demonstrated experience improving build, release, and deployment automation (CI/CD, containerization, artifact distribution, etc.)
    • Familiarity with AWS services (S3, EC2, Lambda, DynamoDB) or equivalent cloud services.
    • Experience working with instrument control software, laboratory automation, or other hardware/software interfaces.
    • Solid understanding of modern software architectures (e.g., hexagonal, service-oriented).
    • Familiarity with databases (SQL and NoSQL) and data pipeline design.
    • Ability to collaborate effectively across software, hardware, and scientific teams.
    • BS/MS in Computer Science, Software Engineering, or equivalent experience.
    Nice to Have:
    • Familiarity with ReactJS or similar frameworks.
    • Experience with scientific imaging, genomics, or laboratory instrumentation.
    • Background in product development within a startup or fast-paced R&D environment.
    What Success Looks Like:
    • MERSCOPE instrument software can be deployed safely and repeatably to production instruments several times per year.
    • Build and validation processes are automated and observable, reducing manual QA cycles.
    • The codebase and architecture enable rapid development of new features while maintaining robustness.

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