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Ai Math Training Jobs in California (NOW HIRING)

Sciforium

LLM Training Engineer

San Francisco, CA · On-site

$155K - $220K/yr

About the Role As an LLM Training Engineer , you'll work across the full foundation-model stack ... MS or PhD in Computer Science, Machine Learning, AI, Mathematics, or related field Benefits include

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Ai Math Training information

What are some common challenges faced in an AI Math Training role?

One of the main challenges in an AI Math Training position is translating complex mathematical theories into practical algorithms that can be efficiently implemented in machine learning models. You may also encounter difficulties when training models on large datasets, balancing computational resources with accuracy, and ensuring models generalize well to unseen data. Collaboration with data scientists, engineers, and domain experts is frequent, requiring strong teamwork and communication skills. Staying current with rapidly evolving AI and mathematical techniques is essential for success and ongoing career development in this field.

What are the key skills and qualifications needed to thrive in the Ai Math Training position, and why are they important?

To thrive in an AI Math Training role, you need a strong background in mathematics, statistics, and machine learning, often supported by a degree in mathematics, computer science, or a related field. Experience with programming languages (such as Python or R), deep learning frameworks (like TensorFlow or PyTorch), and relevant AI or data science certifications are typically required. Strong analytical thinking, clear communication, and problem-solving abilities help in conveying complex concepts and collaborating with diverse teams. These skills are essential for effectively developing and training AI models that rely on advanced mathematical principles and for communicating technical findings to both technical and non-technical stakeholders.

What is an AI Math Training job?

An AI Math Training job involves developing, refining, and optimizing mathematical models used in artificial intelligence systems. This role often includes curating datasets, training AI algorithms, and ensuring mathematical accuracy in machine learning models. Professionals in this field typically have expertise in linear algebra, calculus, statistics, and optimization techniques. They work closely with data scientists and engineers to improve AI efficiency and reliability.

What are the most commonly searched types of Ai Math Training jobs in California? The most popular types of Ai Math Training jobs in California are:
What are popular job titles related to Ai Math Training jobs in California? For Ai Math Training jobs in California, the most frequently searched job titles are:
What job categories do people searching Ai Math Training jobs in California look for? The top searched job categories for Ai Math Training jobs in California are:
What cities in California are hiring for Ai Math Training jobs? Cities in California with the most Ai Math Training job openings:
Ai Math Training jobs near you
Infographic showing various Ai Math Training job openings in California as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% In-person, and 13% Remote job distribution.

Hyperbolic Labs - Senior GPU Infrastructure Engineer

De Circle

San Francisco, CA • On-site, Remote

$127K - $173K/yr

Full-time

Posted 3 days ago

Job description

Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By aggregating computing resources across the globe, we offer an innovative GPU marketplace and AI inference service that promise affordability and accessibility for all. As pioneers at the intersection of AI and open-source technology, we believe in an open future where AI innovation is limited only by imagination, not by access to resources. We're looking for forward-thinking individuals who share our passion for making AI universally accessible, secure, and affordable. Join us in building a platform that empowers innovators everywhere to turn their visionary AI projects into reality.
As we prepare for growth after our Series A, our team - led by co-founders with PhDs in AI, Math, and Computer Science - is poised to redefine computing.
About the Role
We're seeking a Senior Infrastructure Engineer to help build and scale Hyperbolic's GPU Cloud Marketplace, by building a multi-tenancy provisioning and virtualization solution. This is a foundational role where you'll be responsible for transforming raw GPUs from diverse global suppliers into a programmable, orchestrated pool that serves thousands of AI developers and researchers. You'll work at the cutting edge of cloud infrastructure, building the core orchestration layer that enables our platform to deliver up to 75% cost savings compared to traditional cloud providers.
Who You Are
  • Deep understanding of bare-metal provisioning and lifecycle management, including IPMI/Redfish, BMC-based remote management, PXE boot, and automated OS deployment workflows
  • Deep understanding of GPU scheduling and orchestration, including GPU type awareness, memory management, topology considerations, placement strategies for multi-GPU jobs, and fragmentation minimization
  • Strong infrastructure and DevOps engineering skills with proficiency in Terraform or Pulumi, CI/CD for infrastructure, secrets management, configuration management, and observability stack implementation
  • Experience with storage and data infrastructure for AI/ML workloads, including object storage, high-IOPS block storage, and distributed file systems for training data and checkpoints
  • Proficiency with API design and cloud-init for automated provisioning and configuration
  • Solid understanding of GPU architecture, CUDA, and GPU compute optimization
  • Highly collaborative team player with excellent communication skills across technical and non-technical stakeholders
  • Proven ability to work effectively with hardware vendors and vendor engineering teams to troubleshoot issues and optimize integrations
  • Experience building and scaling cloud infrastructure or distributed systems in production environments

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