Symbolica is looking to build AI systems that can reason logically like humans, moving beyond traditional data-hungry neural networks. The ML Infrastructure Engineer will design, build, and optimize the infrastructure and tools to support this research and development, accelerating the creation of scalable machine learning models.
Requirements
- 5+ years of experience in software engineering or infrastructure roles, with at least 2 years in machine learning infrastructure or MLOps.
- Proficiency in scaling DevOps pipelines for both traditional software and (based on ArgoCD) as well as MLOps pipelines using orchestration tools like ZenML and Kubernetes.
- Experienced with Linux, containers, Nix, Kubernetes
- Interest in making sure the infrastructure behind our models is secure by design.
Responsibilities
- Expanding and improving our infrastructure for large-scale machine learning workflows, including training systems and model deployment.
- Developing tools and frameworks to support the global team’s experiments, ensuring reproducibility and scalability.
- Optimizing compute resources and ensuring efficient use of cloud and on-prem hardware for training and inference.
- Building and maintaining CI/CD pipelines tailored for machine learning development.
- Collaborating closely with machine learning scientists, researchers and engineers to identify and address infrastructure needs.
Other
- This is an onsite role that can be based in our SF office.
- Exceptional problem-solving skills with the ability to nimbly solve edge-cases with minimum disruption.
- Competitive salary and early-stage equity package.
- A high-trust, execution-first culture with minimal bureaucracy.
- Direct ownership of meaningful projects with real business impact.
- A rare opportunity to sit at the interface between deep research and real-world productisation.
- Symbolica is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, religion, disability, or sexual orientation.
