AI Data Specialist

1 week ago

Austin, Texas, United States Unreal Gigs Full time
Unreal Gigs Seeks an Experienced AI Data Trainer

We are seeking a skilled AI Data Trainer to join our team at Unreal Gigs. As an AI Data Trainer, you will play a crucial role in preparing, labeling, and refining data that directly impacts the performance and learning of AI algorithms across diverse applications.

The ideal candidate will have extensive experience with data annotation tools and techniques, as well as strong analytical skills and quality assurance abilities. You will be responsible for collaborating with cross-functional teams, including data scientists, machine learning engineers, and product managers, to curate, clean, and label datasets.

Key Responsibilities:

  • Data Curation and Labeling: Select, label, and organize datasets to enable machine learning models to learn effectively, ensuring data is representative, balanced, and relevant for the models' intended tasks.
  • Data Refinement and Cleaning: Preprocess and clean raw data to eliminate noise and inaccuracies, applying best practices to enhance data accuracy and reliability.
  • Collaboration on Annotation Guidelines: Work with data scientists and product managers to define labeling and annotation guidelines that align with project goals, standardizing processes to maintain consistency across datasets.
  • Optimizing Data for Model Performance: Analyze and select data subsets to improve model training efficiency and accuracy, monitoring model performance to identify and address gaps in data quality or diversity.
  • Quality Assurance on Labeled Data: Perform quality checks on annotated data to ensure labels are accurate and useful for model training, providing feedback to improve data annotation workflows and tools.
  • Monitoring and Reporting Data Training Results: Track the impact of training data on model performance and create reports to communicate improvements and insights, working closely with machine learning engineers to refine datasets iteratively.

Salary Range: $80,000 - $110,000 per annum, depending on experience. This estimate is based on industry standards and location considerations.

Requirements:

  • Data Annotation and Labeling: Extensive experience with data labeling tools and techniques, with the ability to create high-quality, structured datasets.
  • Data Cleaning and Preprocessing: Strong understanding of data cleaning methods to prepare datasets for model training, handling both structured and unstructured data formats.
  • Analytical Skills and Quality Assurance: Ability to assess data quality and accuracy through quality assurance processes, troubleshooting and refining data to enhance model performance.
  • Collaboration and Communication: Strong communication skills to work with cross-functional teams and explain data requirements, being detail-oriented and organized in managing datasets.
  • Technical Skills: Proficiency in data manipulation using tools like Python or SQL, familiarity with data labeling platforms (e.g., Labelbox, Amazon SageMaker Ground Truth, or Supervisely) is beneficial.

Benefits:

  • Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
  • Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
  • Work-Life Balance: Flexible work schedules and telecommuting options.
  • Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
  • Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
  • Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
  • Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
  • Tuition Reimbursement: Financial assistance for continuing education and professional development.
  • Community Engagement: Opportunities to participate in community service and volunteer activities.
  • Recognition Programs: Employee recognition programs to celebrate achievements and milestones.

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