Symbolica
DevOps Engineering Lead - ML Infrastructure
Symbolica, San Francisco, California, United States, 94199
DevOps Engineering Lead - ML Infrastructure
About Us
Symbolica is an AI research lab pioneering the application of category theory to enable logical reasoning in machines. We’re a well-resourced, nimble team of experts on a mission to bridge the gap between theoretical mathematics and cutting‑edge technologies, creating symbolic reasoning models that think like humans – precise, logical, and interpretable. While others focus on scaling data‑hungry neural networks, we’re building AI that understands the structures of thought, not just patterns in data.
Our approach combines rigorous research with fast‑paced, results‑driven execution. We’re reimagining the very foundations of intelligence while simultaneously developing product‑focused machine learning models in a tight feedback loop, where research fuels application.
Founded in 2022, we’ve raised over $30M from leading Silicon Valley investors, including Khosla Ventures, General Catalyst, Abstract Ventures, and Day One Ventures, to push the boundaries of applying formal mathematics and logic to machine learning.
Our vision is to create AI systems that transform industries, empowering machines to solve humanity’s most complex challenges with precision and insight. Join us, define the future of AI by turning groundbreaking ideas into reality.
About the Role
As a
DevOps Engineering Lead
working closely with our Head of ML Engineering, you will lead the design, build, and optimization of the infrastructure and tools that enable us to take our research and development efforts from the lab into a highly reliable, performant, and secure software stack in production. You'll help accelerate the processes involved in going from research prototypes into production and enterprise‑ready platforms with security, availability, and reliability in mind.
Your work will be at the intersection of research and engineering, ensuring our R&D team has the robust platform they need to push the boundaries of AI, working with our GPU vendors, cloud providers, and on‑prem servers.
This is an
onsite role
based in our SF office (345 California St.).
Key Responsibilities
Maintain a central GitOps repository for stable and safe releases of products and internal research tooling with disaster recovery, security, and automation in mind.
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.
Develop tools and frameworks to support the global team’s experiments, ensuring reproducibility and scalability.
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.
About You
5+ years of experience in DevOps or infrastructure roles, with at least 2 years in machine learning infrastructure or MLOps. It would be a benefit if you have built, maintained, or managed ML infrastructure using DevOps practices in the past.
Proficient in cloud‑native architectures, with the ability to make the right trade‑offs when necessary.
Experienced with Linux, containers, GPU management, Nix, Kubernetes and an interest in making sure the infrastructure behind our models is secure by design.
Exceptional problem‑solving skills with the ability to nimbly solve edge cases with minimum disruption.
Solid software engineering skills in Rust, Golang, or Python.
What We Offer
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 productization.
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.
#J-18808-Ljbffr
Symbolica is an AI research lab pioneering the application of category theory to enable logical reasoning in machines. We’re a well-resourced, nimble team of experts on a mission to bridge the gap between theoretical mathematics and cutting‑edge technologies, creating symbolic reasoning models that think like humans – precise, logical, and interpretable. While others focus on scaling data‑hungry neural networks, we’re building AI that understands the structures of thought, not just patterns in data.
Our approach combines rigorous research with fast‑paced, results‑driven execution. We’re reimagining the very foundations of intelligence while simultaneously developing product‑focused machine learning models in a tight feedback loop, where research fuels application.
Founded in 2022, we’ve raised over $30M from leading Silicon Valley investors, including Khosla Ventures, General Catalyst, Abstract Ventures, and Day One Ventures, to push the boundaries of applying formal mathematics and logic to machine learning.
Our vision is to create AI systems that transform industries, empowering machines to solve humanity’s most complex challenges with precision and insight. Join us, define the future of AI by turning groundbreaking ideas into reality.
About the Role
As a
DevOps Engineering Lead
working closely with our Head of ML Engineering, you will lead the design, build, and optimization of the infrastructure and tools that enable us to take our research and development efforts from the lab into a highly reliable, performant, and secure software stack in production. You'll help accelerate the processes involved in going from research prototypes into production and enterprise‑ready platforms with security, availability, and reliability in mind.
Your work will be at the intersection of research and engineering, ensuring our R&D team has the robust platform they need to push the boundaries of AI, working with our GPU vendors, cloud providers, and on‑prem servers.
This is an
onsite role
based in our SF office (345 California St.).
Key Responsibilities
Maintain a central GitOps repository for stable and safe releases of products and internal research tooling with disaster recovery, security, and automation in mind.
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.
Develop tools and frameworks to support the global team’s experiments, ensuring reproducibility and scalability.
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.
About You
5+ years of experience in DevOps or infrastructure roles, with at least 2 years in machine learning infrastructure or MLOps. It would be a benefit if you have built, maintained, or managed ML infrastructure using DevOps practices in the past.
Proficient in cloud‑native architectures, with the ability to make the right trade‑offs when necessary.
Experienced with Linux, containers, GPU management, Nix, Kubernetes and an interest in making sure the infrastructure behind our models is secure by design.
Exceptional problem‑solving skills with the ability to nimbly solve edge cases with minimum disruption.
Solid software engineering skills in Rust, Golang, or Python.
What We Offer
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 productization.
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.
#J-18808-Ljbffr