Senior Software Engineer

About Pictor Labs

Pictor Labs is the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.

Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

Responsibilities:

• Design and implement REST APIs and web-based applications for PictorLabs cloud services and Pictor Edge device configuration, monitoring, and management
• Develop intuitive web UI for both cloud-based virtual staining workflows and edge device deployment and configuration
• Build and maintain backend services that seamlessly operate across cloud (AWS) infrastructure and edge device environments
• Design and implement efficient database schemas for cloud service management, edge device management, inference job tracking, results storage, and audit logging optimized for low latency responses
• Architect and implement containerized AI/ML inference pipelines for deployment on both cloud infrastructure and edge devices (NVIDIA DGX hardware)
• Isolate and address performance issues end-to-end for large pathology slide images across cloud and edge deployments
• Implement comprehensive observability solutions including telemetry, logging, monitoring, and alerting for distributed cloud and edge deployments
• Write clean and extensible Python, TypeScript, and Node.js code with production-grade security, scalability, and debuggability best practices
• Ensure all software implementations meet FDA compliance requirements (21 CFR Part 11, 820) and SOC2 security standards for both cloud services and edge devices
• Work closely with ML Engineering, ML Research, and Edge Device teams to integrate AI models into production-ready inference services
• Participate in design reviews, code reviews, and architecture discussions to maintain high software quality standards
• Identify performance bottlenecks in inference pipelines, cloud services, and edge-to-cloud communication. Deliver optimized solutions to address them
• Develop and maintain comprehensive technical documentation including API specifications, deployment guides, and security documentation for regulatory submissions
• Participate in on-call rotation, incident management, and root cause analysis to improve system reliability
• Collaborate with QA teams to implement automated testing within CI/CD pipelines for both cloud and edge deployments