Senior Software Engineer

PICTOR LABS INC•Austin, TX

8d•Remote

About The Position

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.

Requirements

Bachelor's Degree (Master's Degree preferred) in Computer Science, Engineering, Mathematics, or related field
5-7 years of software development experience building distributed systems and web applications
4+ years of experience designing and implementing REST APIs and backend services in production environments
3+ years of experience with AI/ML application development, including deploying and optimizing inference services
4+ years of hands-on experience with Python and TypeScript/JavaScript for backend and frontend development
3+ years of experience with cloud infrastructure (AWS preferred) including services such as EC2, S3, EKS, ECR, Lambda, and CloudWatch
3+ years of experience with containerization technologies (Docker, Kubernetes) for both cloud and edge deployments
3+ years of experience with database design and implementation (SQL and NoSQL databases)
2+ years of experience developing software in regulated environments with understanding of FDA and/or SOC2 compliance requirements
Experience with observability platforms and tools (e.g., Prometheus, Grafana, CloudWatch, DataDog, or similar)
Strong understanding of DevOps practices and CI/CD pipelines
Experience with frontend frameworks such as React for building web-based management interfaces
Excellent problem-solving skills and attention to detail
Comfortable with ambiguity and ability to thrive in a fast-paced startup environment
Strong written and verbal communication skills for cross-functional collaboration

Nice To Haves

Knowledge of medical imaging formats and workflows (DICOM, whole slide imaging, digital pathology)
Experience with edge computing architectures and hybrid cloud-edge deployments
Familiarity with ML frameworks such as PyTorch and TensorFlow
Experience with image processing, streaming large binary data and optimizing data transfer between edge and cloud
Knowledge of IEC/ISO standards such as 62304, 14971, 13485, 27001, or UL 2900
Experience with infrastructure-as-code tools (Terraform, CloudFormation, Ansible)
Prior experience in healthcare technology, medical devices, or biotechnology industries
Experience with WebSocket or gRPC for real-time communication
Knowledge of cybersecurity best practices for medical device software

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