What are the responsibilities and job description for the Senior ML Infrastructure Engineer position at Jobright.ai?
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Job Summary:
Symbolica AI operates as a research-focused company, pioneering the application of category theory to enable logical reasoning in machines. The ML Infrastructure Engineer will design, build, and optimize the infrastructure and tools that support the research and development efforts, ensuring a robust platform for machine learning experiments.
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.
Qualifications:
Required:
• 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 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.
Company:
Symbolica AI operates as a research-focused company. Founded in 2022, the company is headquartered in Palo Alto, California, USA, with a team of 11-50 employees. The company is currently Early Stage.
