WHO WE ARE:

For over 20 years, Global Relay has set the standard in enterprise information archiving with industry-leading cloud archiving, surveillance, eDiscovery, and analytics solutions. We securely capture and preserve the communications data of the world’s most highly regulated firms, giving them greater visibility and control over their information and ensuring compliance with stringent regulations.
Though we offer competitive compensation and benefits and all the other perks one would expect from an established company, we are not your typical technology company. Global Relay is a career-building company. A place for big ideas. New challenges. Groundbreaking innovation. It’s a place where you can genuinely make an impact – and be recognized for it.
We believe great businesses thrive on diversity, inclusion, and the contributions of all employees. To that end, we recruit candidates from different backgrounds and foster a work environment that encourages employees to collaborate and learn from each other, completely free of barriers.

YOUR ROLE

As a Data Labeler, you will be part of a small, highly focused team responsible for creating high quality training dataset that we use with our models for building the artificial intelligence and machine learning solutions for Global Relay’s customers. You will be working with a wide variety of data that includes, but not limited to text, audio, and images. You will have an opportunity to collaborate closely with some of the best data scientists and software developers in Vancouver and apply your craft in an environment that encourages creative thinking and collaboration.

YOUR RESPONSIBILITIES

• Create high-quality datasets for models by
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• Gathering: Assist Data Scientist in the gathering of large, representative datasets based on provided criteria.

• Labelling: Label text data. This may include labelling for items such as tone, sentiment, or business theme.
• Transcribing: Annotate and label audio data. This may include transcribing spoken words, identifying speech segments, and labelling various acoustic features.
• Annotation: Add metadata to images, identifying regions of interest.
• Classifying: Categorize data into different categories.
• Identifying: Identify patterns, trends, and outliers in data.
• Creating: Create synthetic data based on patterns, trends, and predictions.
• Reviewing: Review your own work, and that of others, to ensure the highest quality and accuracy in our datasets
• Continuously improve quality of data releases by
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• Defining and maintaining taxonomy for the data format

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• Authoring and maintaining prompts for the model

• Reviewing generated dataset for quality and integrity
• Defining annotation guidelines for the data format
• Testing prompts to verify and improve quality
• Benchmarking datasets
• Contribute to the data generation program by
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• Researching on background information to enhance data accuracy

• Working as part of an agile team on the data releases
• Collaborating with data scientists and developers on the data generation initiative
• Providing and accepting feedback on identified issues with data and tools