出海雷达

影像分析师 - AI/ML训练数据

Imagery Analyst - AI/ML Training Data

AI限定地区(需当地身份)与中国几乎无重叠,需长期倒时差
公司Micro1
薪资$20 - $60/小时
工作地点United States
地域资格限定地区(需当地身份)
时区要求与中国几乎无重叠,需长期倒时差
用工类型contract
发布时间8 天前
数据来源4dayweek.io
前往 4dayweek.io 查看并投递 →
注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
作息提示:与中国几乎无重叠,需长期倒时差。

**Pay:** $20-$60 per hour (USD).

Role Title: Imagery Analyst - AI/ML Training Data

Role Type: Contractor (Part-time or Full-time)

Location: Remote, US-based.

micro1 is engaging Imagery Analyst - AI/ML Training Data experts to contribute to a high-impact customer project centered on drone and maritime sensor imagery. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Scope of Work

1. Review and refine machine-generated bounding boxes for accuracy on still imagery from drone and maritime sensors.
2. Identify and annotate objects missed by AI models.
3. Label data maintaining consistency and adherence to provided guidelines.
4. Deliver completed annotated images within a secure Navy environment
5. Maintain steady, reliable throughput of completed images; compensation is based on each image submission.
6. Transition to annotation of video frames as the project evolves and expands in scope.
7. Document and communicate any ambiguous cases or guideline questions clearly, demonstrating strong written and verbal skills.

Preferred Qualifications

1. U.S. citizenship and ability to obtain a DoD Common Access Card (CAC) or willingness to engage in the sponsorship process.
2. Demonstrated attention to detail and consistency performing repetitive, accuracy-critical tasks.
3. Experience with data labeling, bounding box annotation, or similar data-preparation activities.
4. Familiarity with aerial, maritime, or sensor-based imagery, especially in daylight and thermal formats.
5. Track record in high-volume, quality-controlled annotation environments (robotics or autonomous system data-labeling experience is a plus).
6. Comfort using dedicated software tools for labeling tasks, with a willingness to learn new applications.
7. Strong written and verbal communication skills for reporting and clarifying labeling requirements.

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