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Data Annotation Manager Jobs in Florida (NOW HIRING)

JPMorgan Chase & Co.

Applied AI/ML Lead

Tampa, FL · On-site

Establish robust MLOps practices and annotation workflows, including model versioning, automated ... design and manage labeling strategies for training data, ensuring high-quality ground truth ...

JPMorganChase

Applied AI/ML Lead

Tampa, FL · On-site

... annotation workflows, including model versioning, automated retraining triggers, A/B testing of ... design and manage labeling strategies for training data, ensuring high-quality ground truth ...

SurGenTec

Marketing Communications Manager

Boca Raton, FL · On-site

$116K - $130K/yr

InDesign (print layout), Illustrator (graphics), and Acrobat Pro (PDF review and annotation ... data • Familiarity with spine anatomy, common procedures (TLIF, PLIF, ALIF, SI joint fusion ...

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$23.2K

$72.6K

$128.5K

How much do data annotation manager jobs pay per year?

As of Jun 1, 2026, the average yearly pay for data annotation manager in Florida is $72,595.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,300.00 and $93,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Annotation Manager, and why are they important?

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

What are some common challenges faced by Data Annotation Managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Florida? The most popular types of Data Annotation jobs in Florida are:
What are popular job titles related to Data Annotation Manager jobs in Florida? For Data Annotation Manager jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in Florida look for? The top searched job categories for Data Annotation Manager jobs in Florida are:
What cities in Florida are hiring for Data Annotation Manager jobs? Cities in Florida with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you
Applied AI/ML Lead

Applied AI/ML Lead

JPMorgan Chase & Co.

Tampa, FL • On-site

Full-time

Medical, Retirement

Posted 27 days ago

JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 467 frontline employees who took The Breakroom Quiz

47th of 141 rated banks

Job description

Job Description
As Applied AI/ML Lead within Commercial & Investment Bank with the Healthcare Provider team, you will lead the design, development, and production deployment of AI/ML solutions focused on image classification, text categorization, and data extraction from scanned TIF documents. You will architect and implement computer vision pipelines leveraging CRNN architectures for document type identification, page-level categorization, and visual feature extraction.
Job responsibilities
  • Lead the design, development, and production deployment of AI/ML solutions focused on image classification, text categorization, and data extraction from scanned TIF documents and evaluate and explore additional models and architectures to continuously improve classification accuracy, extraction quality, and processing efficiency.
  • Drive the development and fine-tuning of models for document understanding, text categorization, named entity recognition, and semantic understanding and combine visual layout information, textual content, and spatial relationships to extract structured data from complex scanned documents, while enabling automated categorization and metadata tagging of OCR-extracted text.
  • Lead the integration and optimization of OCR technology and generative AI capabilities into the document processing pipeline, ensuring high-accuracy text extraction from scanned TIF images across diverse document types, layouts, fonts, and quality levels. Leverage Amazon Bedrock to explore foundation model capabilities for intelligent document understanding, classification, document summarization, and augmenting traditional extraction pipelines.
  • Architect and implement scalable ML training and inference pipelines using AWS SageMaker, managing model training, hyperparameter tuning, distributed training for large vision models, and real-time/batch inference endpoint deployment. Collaborate with software engineering teams to integrate trained models into Java/Python-based microservices deployed on AWS EKS, ensuring low-latency, high-throughput inference for production document processing workloads.
  • Establish robust MLOps practices and annotation workflows, including model versioning, automated retraining triggers, A/B testing of model variants, drift detection on document distributions, and comprehensive performance monitoring dashboards and design and manage labeling strategies for training data, ensuring high-quality ground truth datasets for image classification, text categorization, and document extraction tasks.
  • Build and manage a team of ML engineers and applied scientists, fostering a culture of experimentation, rapid prototyping, and rigorous evaluation of model performance against business KPIs.

Required qualifications, capabilities, and skills
  • Bachelor's degree or MS or PhD in quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.
  • 7+ years of experience in applied ML/AI roles with at least 2+ years leading teams or large-scale ML initiatives
  • Advanced proficiency in Python and enterprise languages, with deep experience in PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, and Pillow for model development and image processing. Proficiency in Java and/or Groovy for integrating ML capabilities into backend services and enterprise application ecosystems. Familiarity with Oracle databases for feature extraction, training data retrieval, and integration with ML workflows.
  • Deep expertise in computer vision and NLP models, with hands-on experience implementing and fine-tuning CRNN-based architectures for image classification and feature extraction. Strong experience with multimodal document understanding combining text, layout, and image features. Proficiency in transformer-based NLP models for text categorization, sequence labeling, named entity recognition, and semantic analysis of OCR-extracted content.
  • Practical experience with OCR technologies and image preprocessing, for text extraction from scanned documents, with an understanding of OCR accuracy optimization, preprocessing techniques, and post-processing correction. Experience with image preprocessing for scanned documents in TIF format, including multi-page handling, resolution normalization, deskewing, binarization, and noise removal.
  • Deep hands-on experience with AWS SageMaker and Amazon Bedrock, including end-to-end ML workflows such as training jobs, processing pipelines, model registry, distributed training, and real-time/batch inference endpoints. Practical experience leveraging foundation models, prompt engineering, and building generative AI-augmented document processing solutions. Experience deploying and scaling ML models as containerized microservices on AWS EKS using Docker and Kubernetes, with expertise in optimizing GPU-based inference workloads.
  • Strong knowledge of MLOps tools and practices, including MLflow, SageMaker Pipelines, or equivalent platforms for experiment tracking, pipeline automation, and model lifecycle management. Excellent leadership and communication skills with the ability to present complex technical concepts to senior leadership and non-technical audiences.

Preferred qualifications, capabilities, and skills
  • Domain expertise in the healthcare industry
  • Experience in applied ML/AI roles in document processing, computer vision, or NLP domains

About Us
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
About the Team
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

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