Senior Software Engineer, Cleerly

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field (or equivalent experience)
• 8–12 years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar)
• Demonstrable capability in designing, implementing, and securing RESTful web services
• Experience in MLOps orchestration and cloud deployment (Docker, Kubernetes)
• Experience with AWS, GitHub, and continuous integration pipelines
• Proven track record of architecting and delivering scalable systems in production environments
• Experience mentoring engineers and raising the technical bar through reviews and design feedback
• Strong systems thinking with the ability to evaluate tradeoffs in scalability, reliability, and maintainability
• Experience designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks)
• Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders

Desirable

• We're seeking a Senior Software Engineer to drive key technical initiatives across our computational imaging pipeline
• In this high-impact role, you'll own the complex systems responsible for deploying, scaling, and monitoring our regulated AI algorithms end-to-end
• You will influence the architecture of our system, ensuring our solutions meet medical standards for quality and performance, while mentoring other engineers and helping shape our technical culture
• You will join our expert Computational Imaging team, where we develop sophisticated algorithms to enhance and improve medical imaging
• We are focused on improving the quality and clinical value of medical images, creating powerful, extra software components that correct artifacts, standardize data, and ensure the utmost precision before the final analysis
• Our work is essential for elevating the reliability and accuracy of Cleerly’s regulated products
• Design, build, and deploy scalable AI services and computational imaging pipelines to production, ensuring robust, high-availability infrastructure for our machine learning algorithms
• Design extensible system architectures and make pragmatic trade-offs that balance performance, security, and maintainability
• Own full lifecycle delivery of complex features, from architectural planning and API design to implementation and post-release observability
• Ensure high availability and observability of our services; improve alerting, logging, and incident response across the stack
• Set and uphold strong engineering standards via code reviews, technical mentorship, and design documentation
• Lead technical design reviews and system decomposition efforts across teams
• Proactively identify risks and gaps in operational or architectural resilience, and drive durable improvements
• Collaborate closely across AI and engineering to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation
• Design and implement robust testing mechanism and validation strategies to ensure compliance with our Quality Management System and regulatory standards
• Contribute to the necessary technical documentation required for regulatory submissions