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Day Data Annotation Jobs in Missouri (NOW HIRING)

Data Curation & Annotation Systems: Build robust internal QC, mapping, and annotation platforms ... We value high agency--shipping high-quality features in days, not months. * Consumer-Facing ...

Performs annotation and clipping of long-term video EEG data independently (academic locations only ... Tuition Assistance available on first day * BJC Institute for Learning and Development * Health ...

Performs annotation and clipping of long-term video EEG data independently (academic locations only ... Tuition Assistance available on first day * BJC Institute for Learning and Development * Health ...

Day Data Annotation information

What is a day data annotation job?

Day Data Annotation jobs involve reviewing and tagging data, such as images, text, audio, or video, during regular daytime hours. Annotators help prepare datasets for machine learning and artificial intelligence by labeling or categorizing information according to specific guidelines. This work is essential for training algorithms to recognize patterns, objects, or language. Day Data Annotation can be done remotely or in-office, and it often requires attention to detail and good communication skills.

What are the key skills and qualifications needed to thrive as a day data annotation specialist?

To excel as a Day Data Annotation Specialist, you need strong attention to detail, data entry accuracy, and a solid understanding of the subject matter being annotated, often supported by a high school diploma or relevant experience. Familiarity with annotation tools, spreadsheets, and data management software is typically required. Excellent concentration, time management, and clear communication skills help professionals stand out in this role. These abilities are crucial to ensure high-quality, consistent data labeling that directly impacts the performance of machine learning models and downstream business applications.

What are some common challenges faced by day data annotation specialists and how can they be addressed?

Day Data Annotation specialists often encounter challenges such as maintaining high accuracy while handling repetitive tasks, interpreting ambiguous data, and meeting tight deadlines. To address these, it's important to develop strong attention to detail, use project guidelines as references, and communicate with team leads or peers when uncertainties arise. Many organizations also provide regular feedback and quality assurance checks, which help annotators improve their performance and consistency over time.

What is the difference between Day Data Annotation vs Data Labeler?

AspectDay Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, collaborative teamsRemote or on-site, independent work
Industry UsageAI/ML companies, tech firmsAI/ML, data processing companies
Job FocusAnnotating data for machine learning modelsLabeling data to train AI systems

Day Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI. Day Data Annotation often involves more detailed annotation tasks, while Data Labelers may perform broader labeling activities. Both roles require basic technical skills and are vital in AI development across tech industries.

Can I do data annotation with no experience?

Day data annotation jobs often do not require prior experience, as training is typically provided to teach you how to label data accurately. Basic computer skills and attention to detail are usually sufficient to start, and some roles may require familiarity with annotation tools or platforms. Entry-level positions are common and can serve as a stepping stone to more advanced data-related roles.

What are the most commonly searched types of Data Annotation jobs in Missouri?

The most popular types of Data Annotation jobs in Missouri are:

Software Engineer - CV Tooling

Augmodo

California, MO • On-site

$150 - $190/hr

Other

Medical, Dental, Vision, Retirement

Posted 6 days ago


Job description

Augmodo is building the \"operating system for the physical shelf\" using spatial computing and wearable AI. We provide real-time, store-level insights that were previously impossible to capture. We are moving fast, and we need an applied engineer who combines real Computer Vision expertise with high-velocity front-end tooling to make complex spatial data instantly intuitive and highly actionable.

The Challenge

We are looking for a Software Engineer to own the end-to-end user interfaces, active learning agents, and visual tooling powering our Spatial Platform. This is not just a front-end tools role—it requires a real Computer Vision background. You will leverage your experience building and deploying shippable CV models to build pre-labeling agents, custom models for active learning, functional editors, and model-training environments.

Because you understand what it takes to train production-grade ML models, you know that high-quality data is everything. You will apply that knowledge directly to building optimized, intelligent annotation and curation tools for our internal researchers, algorithms, and external clients.

Key Responsibilities
  • Applied CV for Tooling & Automation: Train and integrate lightweight, custom CV models, active learning workflows, and pre-labeling agents specifically designed to accelerate human annotation and data quality control.

  • Data Curation & Annotation Systems: Build robust internal QC, mapping, and annotation platforms (akin to autonomous vehicle curation pipelines) backed by an intimate understanding of CV data quality and edge cases.

  • Spatial & Planogram Interfaces: Design high-performance front-end interfaces that map raw product images and computer vision metadata directly to physical coordinates on digital retail planograms.

  • High-Velocity Iteration: Build functional editors, POCs, and pre-labeling pipelines rapidly to support active model development. We value high agency—shipping high-quality features in days, not months.

  • Consumer-Facing Simplicity: Translate complex, multi-layered spatial and ML outputs into simple, intuitive visual workflows for non-technical users.

Basic Requirements
  • Computer Vision Background: Hands-on experience building, training, and deploying real-world CV models to production. You understand end-to-end model lifecycles and know what \"high-quality data\" actually looks like.

  • Full-Stack Tooling: Strong expertise in React and TypeScript for interactive front-end tools, combined with deep capability in Python (PyTorch/TensorFlow, OpenCV) for the backend model integration.

  • Tooling & Human-in-the-Loop (HITL) Focus: Demonstrated track record building functional editors, canvas-based systems, active learning loops, or annotation tools powered by embedded ML/CV.

  • Bias for Action: High-velocity execution style. You are action-oriented, love leveraging modern AI tools (Cursor, Copilot, etc.), and prioritize getting working tools into researchers' hands fast.

Bonus Points
  • Autonomous Systems / Spatial Data: Prior experience in self-driving data curation pipelines, spatial mapping, LIDAR, or 3D bounding workflows.

  • Retail/Logistics Domain: Experience handling SKUs, physical inventory maps, visual shelf data, or complex product catalogs.

  • 3D/Spatial Web Tech: Familiarity with Three.js, WebGL, or GIS libraries for rendering spatial metadata.

Augmodo offers benefits inclusive of medical, dental, vision, and 401k. The salary range for this role is $150,000 USD - $190,000 USD +equity

Augmodo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability status.

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