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Intern Data Annotation Tech Jobs in Calgary, AB (NOW HIRING)

Cgg

Geo-Mechanical Engineer (Intern)

Calgary, AB · On-site

Viridien (www.viridiengroup.com) is an advanced technology, digital and Earth data company that ... The intern will be in charge of documenting the main steps of the proposed workflow, proposing ...

All JobsIntern Data Annotation Tech JobsIntern Data Annotation Tech Jobs in Calgary, AB

Intern Data Annotation Tech information

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning where human annotators label data such as images, text, or audio to train AI models. Interns in data annotation roles perform tasks like tagging and categorizing data using specialized tools, contributing to the development of accurate AI systems.

What are some common challenges faced by Intern Data Annotation Techs, and how can they overcome them?

Intern Data Annotation Techs often encounter challenges such as maintaining consistency in labeling large datasets and understanding nuanced instructions for annotation tasks. To overcome these hurdles, it's important to ask clarifying questions early on, regularly review annotation guidelines, and participate in team discussions about edge cases. Collaboration with more experienced annotators and feedback from supervisors also help in refining skills and ensuring high-quality data preparation. Developing attention to detail and adaptability will contribute to a successful internship experience.

Does data annotation tech really pay?

Data annotation technicians typically earn hourly wages that vary by experience and location, with entry-level positions often paying minimum wage or slightly above. The pay can increase with skill development, familiarity with annotation tools, and the complexity of the data being labeled. Overall, data annotation jobs provide a modest income but are generally not high-paying roles.

What is the difference between Intern Data Annotation Tech vs Intern Data Labeler?

AspectIntern Data Annotation TechIntern Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentData annotation platforms, remote or officeData labeling platforms, remote or office
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnnotating data for training AI modelsLabeling data for machine learning algorithms

Both roles involve preparing data for AI systems, with similar skills and work environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes technical annotation tasks, while 'Data Labeler' is a more general term. Both are entry-level positions vital for training AI models in the tech industry.

What is a data annotation intern?

A data annotation intern is a temporary position where individuals label or categorize data, such as images, text, or videos, to help train machine learning models. The role typically involves using annotation tools and requires attention to detail to ensure data accuracy, often under supervision or with specific guidelines.

Is data annotation tech still hiring?

Data annotation technician roles are currently in demand as companies expand AI and machine learning projects. These positions often require attention to detail and familiarity with annotation tools, and they are available in various industries including tech, healthcare, and automotive. Hiring trends indicate steady opportunities for entry-level and remote data annotation jobs.

What are Intern Data Annotation Techs?

Intern Data Annotation Techs are entry-level professionals, often students or recent graduates, who support machine learning projects by labeling and categorizing data, such as images, text, or audio. Their work is essential for training AI systems, as accurately annotated data helps algorithms learn to make correct predictions. These interns typically use specialized software tools to tag or classify data according to specific guidelines. The role requires attention to detail, consistency, and sometimes basic technical skills, depending on the complexity of the data and tasks. Internships in data annotation can provide valuable exposure to the fields of artificial intelligence and data science.

What are the key skills and qualifications needed to thrive as an Intern Data Annotation Tech, and why are they important?

To thrive as an Intern Data Annotation Tech, you need attention to detail, basic data management skills, and familiarity with data labeling concepts, often supported by a high school diploma or ongoing college coursework. Experience with annotation platforms, spreadsheet tools, and sometimes basic scripting languages is helpful. Strong communication, reliability, and the ability to follow detailed instructions are valuable soft skills in this role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable machine learning models.
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Intern Data Annotation Tech jobs near you
Software Engineer, ML Infrastructure

Software Engineer, ML Infrastructure

Serve Robotics

Calgary, AB • Remote

$155K - $190K/yr

Full-time

Posted 14 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

Compensation Range: $155K - $190K