Cleerly is a healthcare company revolutionizing heart disease diagnosis and treatment. They are seeking a Senior Software Engineer to drive key technical initiatives across their computational imaging pipeline, owning the systems responsible for deploying and monitoring AI algorithms.
Responsibilities:
- 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
Requirements:
- 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
- Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements
- Hands-on experience with Computer Vision and Deep Learning techniques used for medical image processing