Cleerly is revolutionizing how heart disease is diagnosed, treated, and tracked by developing AI-driven precision diagnostic solutions to prevent heart attacks. The company needs to deploy, scale, and monitor its regulated AI algorithms end-to-end, ensuring solutions meet medical standards for quality and performance.
Requirements
- 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 designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks).
- Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements.
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.
Other
- 8–12 years of software engineering experience
- 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.
- Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders.
- Hands-on experience with Computer Vision and Deep Learning techniques used for medical image processing.
