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Data Annotation For Ai Jobs in Delaware (NOW HIRING)

AI is the primary builder of the Fabric, not merely its consumer. This leader deploys agents that ... annotation at enterprise scale. Responsible for * Certified, versioned data products and semantic ...

AI is the primary builder of the Fabric, not merely its consumer. This leader deploys agents that ... annotation at enterprise scale. Responsible for * Certified, versioned data products and semantic ...

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Data Annotation For Ai information

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.
What are popular job titles related to Data Annotation For Ai jobs in Delaware? For Data Annotation For Ai jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Data Annotation For Ai jobs in Delaware look for? The top searched job categories for Data Annotation For Ai jobs in Delaware are:
What cities in Delaware are hiring for Data Annotation For Ai jobs? Cities in Delaware with the most Data Annotation For Ai job openings:
Infographic showing various Data Annotation For Ai job openings in Delaware as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Hybrid job distribution.

Data Domain Architect Lead

JPMorgan Chase & Co.

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 4 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

73rd of 170 rated banks


Job description


Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop solutions which both our customers and employees can benefit from. Customers expect tailored servicing and Chase is looking to deliver personalization to meet their needs. This is powered by high-quality annotated data and detailed annotation schemes that are the backbone of impactful Artificial Intelligence/Machine Learning ( AI/ML)L algorithms and applications.
As a Data Domain Architect Lead within the Data Annotation team , you will use your domain expertise and people-leading experience to partner your team closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other linguistic resources to help train machine learning models, drive insight, analysis, and possible content creation.
Job responsibilities
  • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
  • Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
  • Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
  • Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
  • Actively contribute to the team's continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group

Required qualifications, capabilities, and skills
  • 6+ years of related experience in development of machine learning solutions
  • Familiar with industry annotation and labeling methods
  • Experience with various data modeling techniques and tools
  • Familiar with Finance and Banking products
  • Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience using Python in working with and analyzing large real-world datasets
  • Working knowledge of information and data retrieval
  • Working knowledge of machine learning and artificial intelligence paradigms and libraries
  • Familiar with Large Language Models (LLMs) and prompt engineering

Preferred qualifications, capabilities, and skills
  • Masters or PhD in a related field, or Bachelors
  • Technical understanding of common relational database systems; i.e., Teradata and Oracle
  • Excellent command of the Structured Query Language (SQL)
  • Knowledge of SAS or Scala, and Python languages
  • Knowledge of Advanced Statistics
  • Advanced analytical thinking and problem-solving skills
  • Strong interpersonal & communication skills

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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