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Internship Data Classification Jobs in Florida (NOW HIRING)

Detect

AI Engineer - Computer Vision

Miami, FL · On-site

... classification on real-world infrastructure imagery. * Support MLOps and data pipelines ... Demonstrated experience through internships, research, or substantial projects is acceptable.

Detect

AI Engineer - Computer Vision

Miami, FL · On-site

... classification on real-world infrastructure imagery. * Support MLOps and data pipelines ... Demonstrated experience through internships, research, or substantial projects is acceptable.

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Staff Accountant

Miami, FL · On-site

$55K - $65K/yr

Review accounts payable and receivable transactions to ensure accurate classification within the ... Internship or up to 1 year of accounting experience preferred * Proficiency in Microsoft Excel and ...

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Internship Data Classification information

What is the difference between Internship Data Classification vs Data Analyst?

AspectInternship Data ClassificationData Analyst
Required CredentialsTypically pursuing or recent graduate, some knowledge of data conceptsBachelor's degree in data-related field, some roles require certifications
Work EnvironmentInternship setting, entry-level tasks, supervisedFull-time, professional environment, independent analysis
Employer & Industry UsageInternship programs in tech, finance, healthcareAcross industries, including tech, finance, marketing
Search & Comparison IntentLearning about entry-level data roles, internshipsUnderstanding data analysis careers, job requirements

Internship Data Classification is an entry-level, supervised role focused on learning data categorization tasks during an internship. In contrast, a Data Analyst is a full-time professional responsible for analyzing data to inform business decisions. While both roles involve working with data, internships are designed for skill development, whereas data analysts perform independent, ongoing analysis in a professional setting.

Internship Data Classification jobs near you
AI Engineer - Computer Vision

AI Engineer - Computer Vision

Detect

Miami, FL • On-site

Other

Posted 9 days ago

Job description

Why Join Us?
  • Growth: With a strong emphasis on personal development, we encourage continuous learning and tackling challenging projects that contribute to your professional growth.
  • Impact: Play a pivotal role in shaping the future of our technology and products, directly influencing the success of our solutions.
  • Culture of experimentation: We live by the mantra "fail fast, fail often". By encouraging experimentation and learning from each failure, we pave the way for significant breakthroughs. We promote an environment where every team member is empowered to test new ideas, challenge the status quo and contribute to a culture of continuous innovation.
What you will do:

As a AI Engineer on the Computer Vision team, your primary focus will be contributing to the development and evaluation of cutting-edge computer vision models and infrastructure that power our AI-driven inspection platform. You'll work alongside experienced engineers to tackle real-world problems in object detection, semantic segmentation, and image understanding. Here's a closer look at your responsibilities:

  • Experiment with and prototype computer vision models: Design, train, and evaluate deep learning models for object detection, segmentation and classification on real-world infrastructure imagery.
  • Support MLOps and data pipelines: Collaborate with the team to improve data preprocessing pipelines, model evaluation tools, and ML lifecycle tracking systems using tools like MLflow.
  • Perform error analysis and quality improvements: Analyze failure modes in models and datasets, and contribute to strategies for improving performance across edge cases.
Growth and Exploration Opportunities:
  • Advanced CV architectures: Explore and test state-of-the-art vision architectures including transformer-based vision models (e.g. ViTs, DINOv2, SAM3).
  • Production AI exposure: Gain hands-on experience in taking AI models from experimentation to deployment, including learning about dataset versioning, reproducibility, and model performance monitoring in production-like environments.
Requirements:
  • Experience building and deploying machine learning or computer vision solutions in real-world environments (production systems, customer-facing products, or internal platforms). Demonstrated experience through internships, research, or substantial projects is acceptable.
  • Strong foundation in computer vision and deep learning, with hands-on experience in areas such as object detection, semantic segmentation, or image classification.
  • Proficiency in Python and practical experience with deep learning frameworks such as Pytorch or Tensorflow
  • Experience working with end-to-end ML workflows, including data preprocessing, model training, evaluation, and iteration.
  • Comfortable working in ambiguous problem spaces and translating real-world constraints into technical solutions.
  • Strong communication skills and the ability to collaborate effectively with engineers, product, and operational teams
Nice to Have:
  • Experience deploying or supporting ML models in production (e.g., APIs, batch inference pipelines, edge deployment, or cloud-based systems).
  • Hands-on experience with MLOps tooling such as MLflow, Weights & Biases, DVC, or similar experiment tracking and lifecycle tools.
  • Familiarity with cloud platforms (GCP, AWS, or Azure) and containerized workflows (Docker).
  • Experience with large-scale or high-resolution imagery, including aerial, satellite, or infrastructure inspection data.
  • Experience improving model performance through data-centric approaches (dataset curation, labeling strategies, augmentation).
Details:
  • Location: Miami (In Office)
  • Salary range: 90k-120k USD
  • Note: This role is open to both junior and senior candidates. Scope, ownership and compensation will be calibrated based on experience.

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