Data Qa And Labelling Specialist

3 weeks ago


Auckland, New Zealand Cropsy Technologies Ltd Full time

Working with global enterprise companies, Cropsy is on a mission to revolutionise the wine-growing industry worldwide. We're growing our operations across the US and NZ and are looking for outstanding people to join us on this exciting journey. You will have the opportunity to work in state-of-the-art technology, solving real-world problems for global customers. RoleCropsy requires a detail-oriented and proactive Data QA and Labelling Specialist to join our team. This is an entry-level role and involves managing the quality assurance of incoming data and efficiently labelling datasets for machine learning models. In this role, attention to detail is critical. You will be working with large datasets where accuracy is paramount. A meticulous approach to both labelling and data QA is essential to maintain high standards across all projects. Additionally, the role involves handling repetitive tasks such as labelling large volumes of data and conducting daily data checks. We expect you to perform these tasks efficiently while maintaining precision. Developing ways to streamline your workflow or improve automation is encouraged, but you must also be comfortable with the routine nature of some responsibilities. Success in this role requires a combination of consistency, speed, and focus. If you do succeed in this role, there are huge opportunities for growth within our small but exceptional team. We highly value initiative, and strong performers are quickly granted higher-level responsibilities. By proving yourself in this entry position, you will have the chance to expand your skill set into areas such as model training, algorithm development, model deployment, and AI strategy. As we grow, you'll be a key part of larger projects, gaining experience in cutting-edge AI technologies and having direct impact with Cropsy customers. This is a fantastic opportunity to accelerate your career in AI and data science with the support of a talented and dedicated team. DutiesYour duties and responsibilities include, but are not limited to - Label Image Datasets: Accurately label image and geospatial datasets for training AI models, ensuring consistency and precision in the labelling process. Improve Labelling Tools: Write code and scripts to enhance in-house labelling tools, optimising efficiency and functionality. Enhance Labelling Processes: Work with the AI and data team to develop and refine labelling workflows, introducing new methods to improve accuracy and speed. Understand and apply guidelines for data annotation, identify issues, and provide feedback to improve annotation strategies and guidelines. Quality Assurance for Labelling: Review labelled data to ensure it meets internal standards and guidelines, correcting inconsistencies or errors where needed. Collaborate on Labelling Standards: Work closely with the AI team to define and maintain consistent annotation guidelines and criteria. Improve AI Workflows: Assist the data science team in automating data handling processes to improve the performance of Cropsy's AI systems, such as working with model-assisted labelling, Cropsy's labelling platform, Cropsy's retraining pipeline, ground-truthing and corrections pipeline, and others. Maintain Data Integrity: Ensure all datasets are stored in a clean, accurate, and properly formatted way for further analysis or model training. Daily Data Monitoring: Perform daily checks on incoming data from field devices, ensuring timely identification of errors or inconsistencies using in-house monitoring tools. Report Data Quality Issues: Actively notify the team when data quality issues are identified, providing details for swift resolution. Run Data Processing Scripts: Execute scripts for data preprocessing, cleaning, and transformation as part of the regular data pipeline. Improve Data Processing Tools: Develop and optimise data validation and processing scripts to enhance automation, speed, and accuracy of data management. You will also be expected to: Keep documentation and records of your work on Notion for system overviews, issues, fixes, planned improvements, etc.Ask for advice and help when you need it, and communicate regularly and openly with the rest of the team.Develop deep technical knowledge of the areas you're working on, so others can come to you for advice.Gain an in-depth understanding of how labelling impacts the AI workflow and contribute improvements to Cropsy's labelling platform.Gain an in-depth understanding of geospatial and crop imagery data and contribute improvements to Cropsy's geospatial data processing pipeline, including the Space Rows process.Gain an in-depth understanding of viticultural knowledge to support your duties.Have an eagle-eyed approach to data labelling and tasks QA tasks.Complete tasks independently and seek guidance from the wider team when needed.Work closely with a multidisciplinary team of data scientists, engineers, and domain experts to develop and deploy cutting-edge solutions that drive outcomes for Cropsy's customers. PreferredA degree in a data or an AI-related field with an A- GPA or higher.Python data stack proficiency.Comfortable with Linux and bash.GIS knowledge. We work in a hybrid home/office split schedule where the entire team is in the office on Monday, Wednesday, and Friday. Half the team works in-office every day. This role will require in-office presence for the first 3-6 months depending on on-boarding progress and competency.  New Zealand valid work visa or residency is required for this position. We are unable to respond to any overseas-based candidates.



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