Job Description
Cloudinary empowers companies to deliver exceptional digital experiences by managing the entire media lifecycle at scale. Within Cloudinary’s R&D, the
Research Group leads the development of cutting-edge algorithms for media understanding, generation, and optimization.
We are seeking an experienced
Staff Backend Engineer to lead the engineering efforts behind our homegrown platform for serving and operating production-grade AI models and AI based algorithms.
This is a
mission-critical role for someone passionate about building highly-scalable, GPU-aware, cloud-native systems that act as the connective tissue between algorithm research and product innovation. You will play a pivotal part in re-designing and evolving the platform, while supporting both research and application teams across the organization, and contributing to MLOps initiatives.
Key Responsibilities
- Own the architecture, stability, scalability, and performance of the system.
- Design and implement platform features that support both synchronous low-latency and asynchronous compute-heavy algorithm execution.
- Enhance GPU management, scheduling, and resource allocation for optimal performance and cost-efficiency.
- Ensure robust Kubernetes-based deployment and observability for a highly dynamic system.
Cross-Team Collaboration- Act as the technical bridge between Research and Application teams by translating requirements into scalable system designs.
- Collaborate closely with algorithm developers to streamline model deployment processes.
- Partner with backend engineers (primarily working in Ruby and Go) to integrate the research group algorithms into Cloudinary services.
Engineering Excellence- Advocate for high standards in code quality, observability, testing, and security.
- Guide engineering integration efforts when consuming the different platform APIs.
- Provide mentorship, support, and best practices to other engineers interacting with the platform.
- Take part in general R&D efforts, supporting a broader production environment.
Platform Extension and MLOps- Contribute to the evolution of our platform to support a wider range of algorithmic workloads and model types.
- Help shape tooling and infrastructure for model versioning, rollout, monitoring, and testing.
- Collaborate with DevOps and Infrastructure teams to maintain operational excellence, system observability, and robust infrastructure support
Your Qualifications
- 8+ years of experience in software engineering, with 3+ years working on infrastructure/platforms involving ML/AI, GPU, or data-heavy systems.
- Proficiency in Python and familiarity with backend languages such as Ruby and/or Go
- Strong understanding of Kubernetes internals and experience running GPU workloads in production environments.
- In-depth knowledge of AWS services
- Experience architecting systems that support both real-time and asynchronous processing pipelines.
- Familiarity with the ML lifecycle and MLOps practices, including CI/CD for models, monitoring, and rollback strategies.
Bonus Qualifications
- Experience working in research-driven environments or alongside data scientists, algorithm research team and ML engineers.
- Contributions to open-source projects related to model serving, Kubernetes operators, or ML platforms.
- Experience supporting systems with diverse user groups across engineering and research disciplines.
Why Join Us?
- Opportunity to build and scale a one-of-a-kind platform powering state-of-the-art media algorithms.
- Collaborate with world-class research, engineering, and product teams.
- Have a direct impact on product experiences used by millions of developers and end-users.
- Be part of a culture that values creativity, autonomy, and continuous improvement.
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