German-Speaking Data Labeling Analyst for AI Speech

Welo Data; California (MO); On-site; USD 52,000 - 58,000; Full time

Benefits offered by this job

Paid Sick Time & Paid Holiday (combined): 15 days

Medical, Dental, and Vision Insurance

Health Savings Account (HSA)

401(k) Retirement Plan

Free breakfast, lunch, and dinner

Stocked micro-kitchens with snacks and beverages

Commuter benefits

Job summary

Welo Data is seeking a Data Labeling Analyst in California. This full-time position involves executing data labeling for speech and voice AI systems, requiring strong judgment and attention to detail. Applicants must have professional-level fluency in German and 1-2 years of relevant experience. Benefits include health insurance, paid holidays, and on-site perks like meals and commuter options. This is a critical role in building AI systems, providing foundational experience in data operations.

Qualifications

• 1–2 years of experience in data labeling, annotation, or content-focused work.
• Comfort working in structured, process-driven environments.
• Basic familiarity with AI, speech technology, or language data is a plus.

Responsibilities

• Execute high-volume data labeling and annotation tasks across speech and voice datasets.
• Follow detailed guidelines to ensure consistency, accuracy, and data integrity.
• Maintain strong throughput while meeting quality expectations.

Skills

Professional-level fluency in German

Strong written communication skills

High attention to detail

Ability to follow detailed instructions

Job description

Welo Data is seeking a Data Labeling Analyst in California. This full-time position involves executing data labeling for speech and voice AI systems, requiring strong judgment and attention to detail. Applicants must have professional-level fluency in German and 1-2 years of relevant experience. Benefits include health insurance, paid holidays, and on-site perks like meals and commuter options. This is a critical role in building AI systems, providing foundational experience in data operations.