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Ai Math Jobs in Delaware (NOW HIRING)

Aumni

Applied AI/ML - Vice President

Wilmington, DE · On-site

$125 - $150/hr

Computer Science, Mathematics, Operations Research, Data Science. * 5+ years of experience in Machine Learning and Artificial Intelligence engineering. * Experience in applied AI/ML engineering, with ...

Sony

$50/hr

Master's degree in Computer Science , Electrical Engineering, Applied Mathematics, or related fields. * Proven knowledge and expertise in generative AI applications, including deep generative ...

Sony

$50/hr

Master's degree in Computer Science , Electrical Engineering, Applied Mathematics, or related fields. * Proven knowledge and expertise in generative AI applications, including deep generative ...

Sony

$50/hr

Master's degree in Computer Science , Electrical Engineering, Applied Mathematics, or related fields. * Proven knowledge and expertise in generative AI applications, including deep generative ...

Sony

$50/hr

Master's degree in Computer Science , Electrical Engineering, Applied Mathematics, or related fields. * Proven knowledge and expertise in generative AI applications, including deep generative ...

Sony

$50/hr

Master's degree in Computer Science , Electrical Engineering, Applied Mathematics, or related fields. * Proven knowledge and expertise in generative AI applications, including deep generative ...

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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 Delaware?

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

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

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

What cities in Delaware are hiring for Ai Math jobs?

Cities in Delaware with the most Ai Math job openings:

Ai Math jobs near you
Infographic showing various Ai Math job openings in Delaware as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution.

Applied AI/ML - Vice President

Wilmington, DE • On-site

JPMorgan Chase & Co.
Finance and Insurance • 10K+ employees
Learn more about JPMorgan Chase & Co.external

$200 - $250/hr

Other

Re-posted 28 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

78th of 176 rated banks

Job description

This is a unique opportunity to apply your skills and leadership in a dynamic environment, directly impacting the future of Home Lending through innovative AI/ML solutions. You will be at the forefront of technology, shaping the next generation of intelligent products and services at JPMorgan Chase.

As Applied AI ML Lead at Consumer & Community Banking Tech, you will drive ML and GenAI projects, leveraging expertise to deliver innovative solutions.

Job responsibilities
  • Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
  • Design, develop, and deploy state-of-the-art AI/ML/GenAI solutions to meet business objectives.
  • Architect and implement robust, cloud-native MLOps/LLMOps pipelines and distributed AI/ML infrastructure (AWS, Azure, GCP) for scalable, efficient deployment and monitoring of models in production.
  • Direct the development and deployment of advanced generative AI solutions (LLMs, RAG, NLP, AI Agents) and classical ML models, integrating state-of-the-art techniques into the ML platform to create innovative fintech products.
  • Develop advanced monitoring and management tools to ensure high reliability and scalability of AI/ML systems.
  • Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
  • Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
  • Communicate AI/ML capabilities and results to both technical and non-technical audiences.
  • Build AI Agents and chatbot
  • Stay informed about the latest trends and advancements in the latest AI/ML research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
Required qualifications, capabilities, and skills
  • Bachelor’s degree or MS or PhD in quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.
  • 5+ years of experience in Machine Learning and Artificial Intelligence engineering.
  • Experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
  • Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
  • Extensive hands‑on technical experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, AWS Bedrock, Transformers, LangChain/LngGraph.
  • Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), orchestration tools (Airflow, FastAPI, etc.) and architectural design, implementation, and performance optimization.
  • Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, deep learning, reinforcement learning), and generative model architectures.
  • Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine‑tuning models, prompt engineering, embeddings and context window.
  • Strong collaboration skills to work effectively with cross‑functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
Preferred qualifications, capabilities, and skills
  • Familiarity with the financial services industries.
  • Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
  • Hands‑on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
  • Familiarity with ethical AI, including bias mitigation, explainability and escalation protocols for risky outputs.
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