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Ai Math Jobs in California (NOW HIRING)

Tensordyne

Sr. ASIC EDA Workflow Engineer

Sunnyvale, CA · On-site

Tensordyne is a technology company involved in building AI math, chips, hardware, and software in order to make AI affordable and efficient. Founded in 2017, the company is headquartered in Sunnyvale ...

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Ai Math information

What is an AI Math specialist?

An AI Math specialist is a professional who applies advanced mathematical concepts and techniques to develop, analyze, and improve artificial intelligence algorithms and models. Their work often involves linear algebra, calculus, probability, statistics, and optimization methods to design effective machine learning and deep learning systems. AI Math specialists collaborate with data scientists, engineers, and researchers to solve complex problems, ensure model accuracy, and enhance the performance of AI-driven solutions.

What are the key skills and qualifications needed to thrive as an AI Math specialist?

To thrive as an AI Math Specialist, you need strong mathematical foundations in linear algebra, calculus, probability, and statistics, typically supported by a degree in mathematics, computer science, or a related field. Proficiency with programming languages like Python, experience with machine learning frameworks (such as TensorFlow or PyTorch), and familiarity with data analysis tools are essential. Critical thinking, problem-solving, and effective collaboration are important soft skills for tackling complex challenges and working in interdisciplinary teams. These skills enable the development, implementation, and optimization of robust AI models and solutions.

How does an AI Math specialist typically collaborate with data scientists and software engineers within a project team?

AI Math specialists play a crucial role in multidisciplinary teams by developing mathematical models and algorithms that underpin AI solutions. They frequently work alongside data scientists to refine statistical methods, validate results, and optimize data processing techniques. Collaboration with software engineers is also common, as AI Math specialists help translate theoretical models into efficient, scalable code for production environments. This teamwork ensures that AI systems are both mathematically sound and technically robust, fostering innovation and effective problem-solving.

What is the difference between Ai Math vs Data Analyst?

AspectAi MathData Analyst
Required CredentialsMathematics, Computer Science, AI certificationsStatistics, Data Analysis, Business Intelligence certifications
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness settings, consulting firms, corporate departments
Industry UsageAI development, machine learning projects, researchData interpretation, reporting, decision support

Ai Math professionals focus on developing algorithms and models using advanced mathematics and AI techniques, often working in research or tech environments. Data Analysts interpret data to provide insights and support business decisions. While both roles require analytical skills, Ai Math emphasizes algorithm creation and AI research, whereas Data Analysts focus on data visualization and reporting.

What are popular job titles related to Ai Math jobs in California?

For Ai Math jobs in California, the most frequently searched job titles are:

What job categories do people searching Ai Math jobs in California look for?

The top searched job categories for Ai Math jobs in California are:

What cities in California are hiring for Ai Math jobs?

Cities in California with the most Ai Math job openings:

Ai Math jobs near you
Infographic showing various Ai Math job openings in California as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Senior AI and Quant DevTech Engineer

NVIDIA Gruppe

Santa Clara, CA • On-site

$152 - $287.50/hr

Other

Posted 13 days ago

Job description

We are looking for a software engineer with a strong background in parallel processing and GPU architecture to push the limits of performance at the intersection of AI, high‑performance computing, and financial markets. In this role, you will dive deep into parallel algorithms, GPUs, and sophisticated systems, identifying and eliminating bottlenecks to unlock the full power of the world’s most advanced processing hardware.

You will collaborate with top experts across industry and academia, influence next‑generation platforms, and share your insights with the global developer community.

What you will be doing:
  • Designing and developing groundbreaking techniques to accelerate high‑performance workloads at the intersection of AI, math, and financial systems.
  • Working hands‑on with leading technical experts to analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.
  • Profiling and eliminating performance bottlenecks across the stack—from algorithms to kernels to system‑level behavior.
  • Publishing and presenting your work in conferences, talks, and blogs to educate and inspire the broader developer community.
  • Influencing the design of future hardware architectures, system software, libraries, and programming models by collaborating closely with NVIDIA research, hardware, compiler, and tools teams.
What we need to see:
  • Strong hands‑on experience with CUDA and parallel programming.
  • Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.
  • A Master’s or PhD in Computer Science, Computer Engineering, Electrical and Computer Engineering, or a related field.
  • Fluency in C/C++ and a solid foundation in algorithms and software design.
  • 5+ years of relevant work or research experience.
  • Proven experience improving the performance of large‑scale computational applications on GPUs.
  • Excellent understanding of linear algebra.
  • Strong communication and organizational skills, with a logical approach to problem‑solving and solid prioritization abilities.
Ways to stand out from the crowd:
  • Experience with inference optimization techniques and deploying optimized AI models in production.
  • Experience with TensorRT, TensorRT‑LLM, and cuTile.
  • Experience parallelizing and optimizing machine learning methods such as decision trees, time‑series models, and Monte Carlo simulations.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD – 241,500 USD for Level 3, and 184,000 USD – 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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