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Scientific Machine Learning Jobs in Delaware (NOW HIRING)

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 ...

Role Overview The Data Science Intern will help us to understand the performance of Executive ... Strong foundation in statistics and machine learning concepts (regression, classification ...

Role Overview The Data Science Intern will help us to understand the performance of Executive ... Strong foundation in statistics and machine learning concepts (regression, classification ...

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

Advanced Machine Learning Techniques: Apply state-of-the-art machine learning methodologies ... such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering. * 5+ years ...

Design and develop scalable AI platforms to support various machine learning and deep learning models. * Collaborate with data scientists to understand model requirements and optimize infrastructure ...

Principal Engineer - AI Platform

Wilmington, DE · On-site

$131K - $175K/yr

Design and develop scalable AI platforms to support various machine learning and deep learning models. * Collaborate with data scientists to understand model requirements and optimize infrastructure ...

Principal Engineer - AI Platform

Wilmington, DE · On-site

$131K - $175K/yr

Design and develop scalable AI platforms to support various machine learning and deep learning models. * Collaborate with data scientists to understand model requirements and optimize infrastructure ...

Data Scientist III - FCRM

Wilmington, DE · On-site

$96K - $155K/yr

The Data Scientist III provides technical leadership across the overall Analytics function which ... Experience with machine learning, generative AI, large language models (LLMs), agentic AI, prompt ...

Showing results 41-60

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Delaware?

For Scientific Machine Learning jobs in Delaware, the most frequently searched job titles are:

What cities in Delaware are hiring for Scientific Machine Learning jobs?

Cities in Delaware with the most Scientific Machine Learning job openings:

Infographic showing various Scientific Machine Learning job openings in Delaware as of August 2026, with employment types broken down into 78% Full Time, 7% Part Time, 4% Temporary, and 11% Contract. Highlights an 75% In-person, 11% Hybrid, and 14% Remote job distribution.

Applied AI/ML - Vice President

Aumni

Wilmington, DE • On-site

$120 - $160/hr

Other

Medical, Retirement

Posted 17 days ago


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 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.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans.

Our Consumer & Community Banking Group depends on innovators like you to serve consumers, small businesses, municipalities and non‑profits. You’ll support the delivery of award‑winning tools and services that cover everything from personal and small business banking as well as lending, mortgages, credit cards, payments, auto finance and investment advice. This group is also focused on developing and delivering cutting‑edge mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers. You will drive ML and GenAI projects, leveraging expertise to deliver innovative solutions.

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