Symbolica is looking to solve the problem of bridging the gap between theoretical mathematics and cutting-edge technologies, creating symbolic reasoning models that think like humans, by designing, building, and optimizing the infrastructure and tools that enable research and development efforts to go from the lab into a highly reliable, performant, and secure software stack in production.
Requirements
- 5+ years of experience in DevOps, or infrastructure roles, with at least 2 years in machine learning infrastructure or MLOps.
- Proficient in cloud-native architectures, with the ability to make the right tradeoffs where necessary
- Experienced with Linux, containers, GPU management, Nix, Kubernetes and an interest in making sure the infrastructure behind our models is secure by design.
- Solid software engineering skills in Rust, Golang or Python
Responsibilities
- Focus on improving the reliability and performance of our Lambda cluster and model training pipeline.
- Assist in managing multiple Kubernetes environments across cloud providers
- Maintain and build the internal observability platform across all environments, covering everything from GPUs, AI applications and distributed backend systems.
- Take ownership of our model training and deployment systems, bringing them to a more scalable, production-ready state.
- Aid in building comprehensive CI tests for GitOps repositories and promotion systems
- Build and maintain different environments for research and client facing products according to best practices
Other
- 5+ years of experience
- Onsite role based in SF office
- Competitive salary and early-stage equity package
- High-trust, execution-first culture with minimal bureaucracy
- Direct ownership of meaningful projects with real business impact
