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Ai Math Jobs (NOW HIRING)

Bank Street

Math and AI Coach-Facilitator

Manhattan, NY · On-site

$115K/yr

Position Vacancy - Math and AI Coach/Facilitator (Full-Time) Bank Street Education Center Bank Street College of Education 610 West 112th Street, New York NY 10025 To: The College Community From:

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 ...

Weekday AI

Mathematics PhD AI Trainer

$70 - $140/hr

This role is for one of the Weekday's clients We are seeking experts with advanced training in Mathematics to contribute to a cutting-edge project in collaboration with a leading AI research group.

Outlier

Math Expertise for AI Training

Develop and answer Math-related questions to refine AI understanding * Evaluate and author complex reasoning traces to ensure models follow logical, step-by-step proofs * Assess and rank AI responses ...

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Ai Math information

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$22.5K

$58.8K

$94.5K

How much do ai math jobs pay per year?

As of Jul 15, 2026, the average yearly pay for ai math in the United States is $58,837.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,000.00 and $70,000.00 per year, depending on experience, location, and employer.

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 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.

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 are the key skills and qualifications needed to thrive as an AI Math Specialist, and why are they important?

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.
More about Ai Math jobs
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Ai Math jobs near you
Infographic showing various Ai Math job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $58,837 per year, or $28.3 per hour.

AI System Analyst (AI Monte Carlo)

Saransh Inc

Houston, TX • On-site

Contractor

Re-posted 22 days ago

Job description

Role: AI System Analyst (AI Monte Carlo)
Client address: Houston, TX (Hybrid)
Contract
 
Experience Required: 10-12 years
 
Mandatory skills:
  • AI Monte Carlo
  • Python
     
Key Responsibilities:
  • Solution Architecture: Design and implement advanced Monte Carlo simulation frameworks to solve complex probabilistic problems (e.g., risk assessment, optimization, or predictive forecasting).
  • Client Engagement: Lead discovery sessions with clients to extract and define technical requirements from high-level business goals.
  • Cross-Functional Collaboration: Serve as the primary technical liaison between functional business units and core engineering teams to ensure alignment on deliverables.
  • End-to-End Delivery: Own the full lifecycle of AI development—from algorithmic design and data modeling to deployment and performance tuning.
  • Mentorship & Leadership: Provide technical guidance to junior/mid-level developers while maintaining the self-sufficiency to handle critical individual contributor tasks in agile environments.
Technical Qualifications:
  • Core AI & Math: Expert knowledge of Monte Carlo methods (MCMC, Sequential Monte Carlo, Quasi-Monte Carlo) and their application in AI/ML environments.
  • Programming: Mastery of Python or C++ (high-performance computing experience is a major plus).
  • Infrastructure: Solid understanding of cloud-based AI deployment (AWS, Azure, or GCP) and containerization (Docker/Kubernetes).
  • Strategic Thinking: 10+ years of experience navigating the trade