CVML, Data Operations Engineer
Lisbon, Greater Lisbon, Portugal
iPhone is the most popular camera in the world. In our Camera & Photos organization (C&P), the precise integration of software and hardware has led to features like Memories and Portrait Mode, which deliver magical, user-focused experiences to 1 Billion+ devices. Within Camera and Photos, Computer Vision and Machine Learning group (CVML) is responsible for building machine learning solutions applied to Apple's image and video processing technologies. This includes technology for OS X and iOS system frameworks (e.g. face recognition and scene classification) as well as internal tools. The group combines research and development in a dynamic environment. As apart of our data team, you will be responsible for crafting high quality datasets at scale for all features developed in CVML, and for Camera and Photos teams. We are looking for a polyvalent and passionate person to lead quality assurance (QA) and throughput monitoring on various data annotation projects.
- You should have over a year experience in annotation projects
- Ability to define/design/develop/optimize annotation workflows and QA workflows (anticipate potential failure modes and edge cases, detect anomalies, generalize, synthesize)
- You should be a strong at problem solving & critical thinking, with an eye for innovation and for continuous optimization (quality, cost efficiency)
- Good pedagogy and interpersonal skills
- Experience with photo applications (e.g. PhotoShop)
- Experience with high level programming languages such as Python (in particular for the manipulation of large amounts of images or other types of files)
- Understanding of the challenges associated to building datasets for machine learning R&D (eg coverage, bias)
This position focuses on setting up annotation projects (in-house, outsourced) and on ensuring the quality of the data delivered to R&D. This includes: - Communicate with R&D team to understand expectations and define specs of annotation tasks You will participate in the selection of assets to be included in the dataset - Define annotation workflow (and re-assess it over time), establish guidelines and training material, establish range for time per task - Calibrate task with vendor - Define and continuously adjust QA methodology (eg types of errors, penalties, QA workflow) - Lead QA effort - Track quantities and quality delivered
Education & Experience
Bachelors in Photography, Graphics Design, Computer Science, Mathematics, Physics, or a related field (or equivalent experience).