What will your main responsibilities include?

• Owning the annotation pipelines from raw to annotated ground truth datasets which satisfy both technical and operational constraints
• Working with data from multiple sources and domains, such as text, images, and structured datasets
• Cooperating closely with Product Managers and Tech Leaders across the organisation to gather business needs and requirements for new annotation pipelines
• Preparing guidelines for other teams and improving them by gathering feedback from Annotators and analyzing obtained annotations
• Implementing and improving quality assurance processes for data annotation pipelines, optimizing both cost and quality of delivered datasets
• Analyzing annotated datasets, ensuring their high quality, finding potential biases and risks in using them for training ML models
• Diving into the details including occasionally annotating data yourself, providing feedback for existing tools, and proposing new features

Why is it worth working with us?

• In your daily work you will expand your knowledge by cooperating with people who have hands-on experience in implementation of the ML models at scale unprecedented anywhere else in Poland
• You will have a key role in the process of ensuring a quality and applicability for model training tasks
• You will be part of an interdisciplinary team working intensively with Technology, Business and the AI ​​/ Data Science area

We offer:

• A modern office and cutting-edge tools 
• Informal working atmosphere in a professional team
• A wide selection of non-wage benefits (such as health insurance, life insurance, gym membership - Multisport, and much more) - you choose what you want
• Exceptional learning opportunities, that include a training budget and access to a wide selection of training programs on our internal MindUp platform

We are looking for people who have:

• Demonstrated ability to manage data annotation projects across multiple teams, building sustainable processes, coordinating release schedules and building consensus on difficult issues
• Practical knowledge of typical data annotation methods and quality assurance processes
• Good understanding of machine learning concepts, tasks, and metrics
• Understanding of statistical concepts applicable to data annotation tasks
• Strong verbal and written communication skills with demonstrated experience of creating annotation guidelines
• High organizational skills, strengths in problem solving, issue-resolution, ability to work in a deadline-driven work environment
• High attention to detail and committed to data accuracy
• Proficiency in standard workflow software (JIRA, Excel, etc.) as well as programming languages (e.g. Python, SQL) allowing to efficiently analyze datasets