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Ai Rag Jobs in Delaware (NOW HIRING)

DE · On-site

$122K - $161K/yr

Familiarity with Prompt Engineering for agents/assistants, Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), RAG, and HITL in Agentic Ecosystems. * Knowledge of AI/LLM ...

Senior Legal Counsel

Wilmington, DE · On-site

$135K - $183K/yr

... RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements and/or data processing agreements.

Senior Legal Counsel

Dover, DE · On-site

$139K - $189K/yr

... RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements and/or data processing agreements.

Senior Legal Counsel

Wilmington, DE · On-site

$135K - $183K/yr

... RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements and/or data processing agreements.

Senior Legal Counsel

Dover, DE · On-site

$139K - $189K/yr

... RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements and/or data processing agreements.

Senior Legal Counsel

Dover, DE · On-site

$139K - $189K/yr

... RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements and/or data processing agreements.

Senior Legal Counsel

Wilmington, DE · On-site

$135K - $183K/yr

... RAG") models, large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements and/or data processing agreements.

$139K - $168K/yr

As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and ... RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current Machine ...

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Ai Rag information

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

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

Which AI is best at RAG?

For an AI Rag role, the best AI systems for Retrieval-Augmented Generation (RAG) tasks typically include models like OpenAI's GPT-4, Google's Bard, and Meta's Llama 2, which are capable of integrating retrieval components with language generation. Success in RAG depends on the model's ability to efficiently access and incorporate external data, as well as the implementation of effective retrieval mechanisms and fine-tuning. Skills in natural language processing, knowledge of retrieval systems, and experience with relevant tools are essential for this role.

What engineer makes 500,000 a year?

Senior software engineers, especially those working in high-demand fields like artificial intelligence or machine learning at large tech companies, can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, and requires advanced skills, extensive experience, and often a master's or Ph.D. in a related field.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in data science, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership in the field.

What are AI RAGs?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

Which 3 jobs will survive AI?

AI Rag is a role that involves managing and interpreting AI outputs, and jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Examples include healthcare professionals, skilled tradespeople, and roles in education. These jobs often require human judgment, interpersonal skills, and adaptability that AI cannot fully replicate.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What are popular job titles related to Ai Rag jobs in Delaware? For Ai Rag jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Delaware look for? The top searched job categories for Ai Rag jobs in Delaware are:
What cities in Delaware are hiring for Ai Rag jobs? Cities in Delaware with the most Ai Rag job openings:
Computational Linguist, Generative AI - Sr. Associate

Computational Linguist, Generative AI - Sr. Associate

JPMorgan Chase & Co.

Wilmington, DE • On-site

$104K - $165K/yr

Full-time

Medical, Retirement

This job post has expired today. Applications are no longer accepted.


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 491 frontline employees who took The Breakroom Quiz

58th of 149 rated banks


Job description


We're looking for a versatile Computational Linguist to join our team focused on evaluating and supporting Generative and Agentic AI systems. This role combines linguistic expertise, data analysis, and hands-on experimentation with large language models.
This role is ideal for someone who can move between qualitative language analysis and quantitative evaluation. You'll work cross-functionally with Machine Learning Engineers, Analytics team and annotators to design innovative, rigorous, and scalable evaluation processes for LLM-powered workflows.
Core Responsibilities
• Serve as a subject matter expert, engaging with various stakeholders throughout the product lifecycle, and maintain a strong understanding of the Chase Digital Assistant's model from both customer and technical perspectives.
• Manage, monitor, and evaluate and version the Chase Digital Assistant's intent and entity taxonomy and the model training; Enforce taxonomy versioning practices to ensure traceability and rollback capability
• Work closely on the adaptation to LLM-driven workflows, ensuring seamless integration of LLMs with existing conversational AI architectures and event tracking systems.
• Implement and evolve metrics and KPIs across Model Correctness, Customer Experience, AI Assurance, and Business Metrics and ensure evaluation is transparent, repeatable, and release-decision-ready
• Maintain established metrics and introduce new guardrail metrics for LLM and generative use cases
• Manage full artifact suite for LLM models including descriptions, prompts, evaluation rubrics, LLM-as-judge prompts, guidelines, calibration data, data statistics & reliability measures.
• Apply ontology design principles to improve semantic reasoning and data integration aligned to business standards.
• Design frameworks to incorporate knowledge graphs within classification and extraction model architectures.
• Align knowledge models with RAG pipelines and agent orchestration to enhance AI functionality.
• Work with data scientists, software engineers, and business stakeholders to translate requirements into robust solutions.
• Identifying optimization opportunities across teams, supporting continuous improvement across model performance, data quality, and feature coverage for improving customer experience.
Required Qualifications, Capabilities, and Skills
• Master's degree in Computational Linguistics, NLP, Linguistics, or related field
• 2+ experience in Computational Linguistics or NLP applied to chatbot or conversational AI development
• Hands-on experience with Generative AI and Agentic AI frameworks and evaluation (e.g., AutoGen, LangGraph, CrewAI, Sierra)
• Linguistic background in discourse & pragmatics
• Advanced knowledge of conversational AI product development lifecycle - training, design, conversation analysis
• Hands-on experience with LLM integration, prompt engineering, evaluation, and performance monitoring
• Proficient in Python, Git, Linux, and Bash scripting
• Fluent with NLP/data science libraries: pandas, numpy, scikit-learn, NLTK
• Experience with transformer-based models (e.g., BERT, GPT) - fine-tuning and application
• Experience with generative AI SDKs and frameworks (e.g., OpenAI, Google, Anthropic, LangChain)
• Comfortable with JSONL, CSV, and Jupyter notebook workflows
• Experience with ontologies/taxonomies and knowledge graphs
• Solid understanding of evaluation methodologies including human-AI comparison and red teaming
• Direct experience with financial institutions, financial products, and customer-facing queries
• Chase customer service experience highly desirable
• Strong written communication for documenting experiments, results, and processes
Preferred Qualifications
• Experience with hybrid conversational architectures, generative AI, and LLM-driven flow design
• Familiarity with LLM safety, bias, and compliance
• Demonstrated success in a highly matrixed organization
• Awareness of current GenAI trends and evaluation challenges in subjective NLP tasks
• Solve the cold start problem via synthetic data generation for new intents, flows, and low-resource scenarios.
About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
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.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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