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Day Shift Ai Data Collection Jobs (NOW HIRING)

Hark

Data Collection

San Jose, CA · On-site

$150K - $250K/yr

While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on ... About the Role You'll own data collection at Hark - the programs, the vendors, and the pipelines ...

Hark

Data Collection

San Jose, CA

$150K - $250K/yr

While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on ... About the Role You'll own data collection at Hark - the programs, the vendors, and the pipelines ...

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Day Shift Ai Data Collection information

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How much do day shift ai data collection jobs pay per hour?

As of Jul 6, 2026, the average hourly pay for day shift ai data collection in the United States is $25.31, according to ZipRecruiter salary data. Most workers in this role earn between $23.32 and $25.96 per hour, depending on experience, location, and employer.

What does a typical day look like for someone working in Day Shift AI Data Collection?

In a Day Shift AI Data Collection role, your day typically involves gathering, labeling, and organizing various types of data—often images, text, or audio—that will be used to train AI models. You'll work closely with data engineers and machine learning teams to ensure the data is accurate, high-quality, and collected according to project specifications. Collaboration with team members is common, especially when troubleshooting data inconsistencies or meeting tight project deadlines. Attention to detail and the ability to follow protocols are crucial, as your work directly impacts the performance of AI systems.

What is the difference between Day Shift Ai Data Collection vs Data Labeling Specialist?

AspectDay Shift Ai Data CollectionData Labeling Specialist
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentOffice or remote; daytime hoursOffice or remote; daytime hours
Industry UsageAI training data collection for machine learningAnnotating and labeling data for AI models
Job FocusGathering raw data through various methodsAdding labels and annotations to datasets

Day Shift Ai Data Collection involves gathering raw data for AI training, while Data Labeling Specialists focus on annotating that data. Both roles often work in similar environments and require comparable skills, but their core tasks differ in data handling stages.

What is a Day Shift AI Data Collection job?

A Day Shift AI Data Collection job typically involves gathering, organizing, and labeling data during regular daytime hours to help train and improve artificial intelligence systems. Workers in this role may be required to collect data from various sources, verify its accuracy, and ensure it is properly formatted for use by AI models. This job is important because high-quality data is essential for developing reliable and effective AI applications. The tasks may include image tagging, audio transcription, or collecting text data, depending on the specific project requirements.

What are the key skills and qualifications needed to thrive as a Day Shift AI Data Collection Specialist, and why are they important?

To excel as a Day Shift AI Data Collection Specialist, you need strong attention to detail, basic data analysis skills, and familiarity with data collection protocols, often supported by a high school diploma or relevant experience. Proficiency with data entry software, spreadsheet tools like Microsoft Excel or Google Sheets, and sometimes specialized data annotation platforms is typically required. Reliability, time management, and effective communication are essential soft skills for maintaining data quality and collaborating with team members. These skills ensure accurate, efficient data gathering which is critical for developing robust AI models and supporting organizational goals.
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Day Shift Ai Data Collection jobs near you
Data Collection

Data Collection

Hark

San Jose, CA • On-site

$150K - $250K/yr

Full-time

Posted 20 days ago

Job description

About Hark
Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.
We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.
To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.
About the Role
You'll own data collection at Hark - the programs, the vendors, and the pipelines that turn raw signal into training data our models can actually learn from.
That means running end-to-end campaigns across human feedback, synthetic data, and product-embedded signals. The quality of what we collect shapes the quality of what we ship, and this role owns that loop.
This is a high-ownership role on a small team. You'll work directly with researchers, engineers, and external partners, and the data you deliver will directly influence how our models behave in the real world.
Responsibilities
  • Design and run data collection programs end-to-end - scoping requirements, writing instructions, defining success criteria, and driving execution with vendors and annotators.
  • Manage external vendor relationships. Be the primary interface between Hark and data partners, keeping quality high and timelines on track.
  • Assess collected data using internal tooling, identify quality issues, and feed clear, actionable feedback back to vendors and annotators.
  • Collaborate closely with model researchers and engineers to understand what data is needed, translate that into operational plans, and deliver.
  • Track program metrics, surface insights, and drive continuous improvements to quality, throughput, and process.
  • Identify gaps in tooling and workflows and propose concrete improvements.

Requirements
  • Operational excellence. You can manage multiple programs simultaneously, keep track of details under pressure, and bring structure to fast-moving situations.
  • Experience working with external vendors or contractors. You know how to set expectations, manage relationships, and hold partners accountable to quality.
  • A knack for data. You've gone beyond surface-level metrics - you dig in, find patterns, and use what you find to make things better.
  • Strong communication. You can translate between research requirements and operational reality, and you keep everyone aligned without letting things slip.
  • Comfort with ambiguity and fast iteration. You take a rough problem, build a process around it, get feedback, and tighten it quickly.
  • Genuine curiosity about AI. You don't need to be an ML researcher, but you care about how models learn and why data quality matters.
  • 2+ years of relevant experience in data operations, program management, or a related field.

Bonus Qualifications
  • Experience managing human feedback or preference data programs.
  • Familiarity with data annotation platforms or labeling pipelines.
  • Experience with synthetic data generation or evaluation dataset design.
  • Background working at a fast-moving AI or research-driven company.

Compensation
The US base salary range for this full-time position is between $150,000 - $250,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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