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Temporary Ai Math Trainer Jobs in California (NOW HIRING)

Unconventional AI

AI Systems, Training

Palo Alto, CA · On-site

$123K - $168K/yr

... training platform and co-design training systems alongside novel AI models and hardware ... Math. • Experience: Veteran of the modern ML software stack. Demonstrated ability to map ...

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Temporary Ai Math Trainer information

What is the difference between Temporary Ai Math Trainer vs Temporary Math Tutor?

AspectTemporary Ai Math TrainerTemporary Math Tutor
Required CredentialsBasic math knowledge, possibly some AI or tech familiarityMath degree or teaching certification often preferred
Work EnvironmentOnline platforms, tech-driven settingsIn-person or online tutoring sessions
Employer & Industry UsageEdTech companies, AI-focused education servicesSchools, tutoring centers, private clients

Temporary Ai Math Trainers focus on leveraging AI tools to assist in math education, often requiring tech familiarity. In contrast, Temporary Math Tutors typically provide direct instruction based on traditional methods. Both roles support student learning but differ in tools and environment used.

What are the typical daily tasks of a Temporary AI Math Trainer, and how do they contribute to AI model development?

As a Temporary AI Math Trainer, your daily tasks often involve reviewing, annotating, and generating math-related data and problem sets to help train and improve AI models. You may be responsible for assessing the accuracy of AI-generated mathematical solutions, providing feedback, and ensuring that the content meets specified quality standards. Collaboration with data scientists and other AI trainers is common to address challenging problems and refine data labeling guidelines. This role is crucial for enhancing the AI's understanding and accuracy in solving mathematical queries, and it provides valuable experience in both education and AI development environments.

What are the key skills and qualifications needed to thrive as a Temporary AI Math Trainer, and why are they important?

To excel as a Temporary AI Math Trainer, you need a solid background in mathematics, analytical thinking, and familiarity with machine learning concepts, often supported by a degree in math, computer science, or a related field. Experience with annotation platforms, data labeling tools, and sometimes programming languages like Python is typically required. Attention to detail, effective communication, and the ability to provide clear, constructive feedback are crucial soft skills in this role. These competencies ensure that the AI models are trained accurately and efficiently, leading to better performance and reliability in mathematical tasks.

What are Temporary AI Math Trainers?

Temporary AI Math Trainers are professionals hired on a short-term basis to help train artificial intelligence systems in understanding and solving mathematical problems. Their tasks typically include evaluating AI-generated math solutions, labeling data, and providing feedback to improve the accuracy and performance of AI models. This role requires a strong understanding of mathematics and attention to detail, as the feedback provided directly impacts the learning process of AI systems. Temporary AI Math Trainers may work for education technology companies, research institutes, or organizations developing AI tools. The position is ideal for individuals with a background in mathematics or teaching who are interested in contributing to the development of educational AI.
What are the most commonly searched types of Ai Math Trainer jobs in California? The most popular types of Ai Math Trainer jobs in California are:
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Temporary Ai Math Trainer jobs near you

Hyperbolic Labs - Senior GPU Infrastructure Engineer

De Circle

San Francisco, CA • On-site, Remote

$127K - $173K/yr

Full-time

Re-posted 26 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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