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Data Annotation information

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

What are the key skills and qualifications needed to thrive in the Data Annotation position, and why are they important?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It typically requires attention to detail and familiarity with annotation tools, and many companies hire remote workers for this role. The job is often part-time or freelance, with varying pay rates depending on complexity and volume of work.
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Data Annotation jobs near you
Software Engineer, ML Infrastructure

Software Engineer, ML Infrastructure

Serve Robotics

Vancouver, WA • On-site, Remote

$155K - $190K/yr

Full-time

Posted 2 days ago

Job description

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
As a Software Engineer on the Machine Learning (ML) Infrastructure team, you will help design, build, and maintain our petabyte-scale data and ML platform that powers data partnerships, ML research, and autonomy engineering. You will build and improve our data discovery capabilities and integrate with 3rd party annotation platforms. By collaborating with members of the autonomy and ml teams you will help us refine how we organize various data attributes and classifications. This role plays a pivotal role in helping the team leverage data from our rapidly expanding fleet of thousands of robots.
Responsibilities
  • Develop and maintain highly scalable data processing pipelines for data curation, annotation, search and ml feature extraction.
  • Build data discovery features for the platform.
  • Create and maintain search features such as natural language querying
  • Develop and maintain our orchestration and scheduling systems.
  • Maintain and evolve our data schemas such as unified data attribute system, scenario tagging and management
  • Build integrations with annotation providers to efficiently review large scale data preannotations
  • Collaborate with autonomy engineers to collect feedback, improve documentation, and run tutorials on platform features

Qualifications
  • BS or MS in computer science with focus in data engineering and/or machine learning
  • 3+ years of industry experience building, running and improving large-volume data processing, feature extraction, data annotation workflows
  • Experience building data mining and search capabilities
  • Experience with both Python and SQL is required
  • Solid understanding of data distributions and their impact on ML Models
  • Hands-on experience and good understanding of LLMs, VLMs, embeddings, vector databases
  • Experience with data annotation providers such as CVAT, LabelBox, LabelStudio, etc

What Makes You Stand Out
  • Experience with integrating cloud inference platforms for LLMs/VLMS (ChatGPT, Gemini, etc)
  • Experience working with Multi Modal data (Lidar, Camera, etc)
  • Experience with robotics systems
  • Experience optimizing large scale vector databases

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