Machine Learning Engineer

hace 2 semanas


Madrid, España Centric Software A tiempo completo

.Engineering - Madrid, Spain - Full TimeCentric Pricing (formerly StyleSage)Centric Pricing is an AI driven competitive assortment benchmarking and market trend insights solution for fashion, beauty and home goods brands and retailers. We are a key innovation partner for iconic and emerging brands across the world.Our Platform analyzes the info of more than 1,000 retailers, processing data from over 600,000 brands, tracking millions of productsThe Data Science team enriches the data collected from fashion-related websites with our own machine learning models. Our models add information to existing products such as categories (clothing, footwear, beauty...), genders, attributes, colors, bounding boxes, etc. Our database contains over 500 million products (growing daily) and we process 1-2 million new products every week.We utilize the latest open-source technologies. We code in Python, using Keras as our main Deep Learning framework (with some projects starting to use Pytorch), along with other machine learning and computer vision libraries like scikit-learn and OpenCV. In engineering, we use Django as our main framework for data access, and our cloud-native code runs in AWS. Our data resides in PostgreSQL databases, monitored with tools like Grafana, InfluxDB, and Telegraf.If you are not familiar with some of these technologies, our engineers will support you on your journey to expertise.Your JobAs a Data Scientist, you will ensure that our current data science pipelines run smoothly and efficiently, as well as develop new machine learning pipelines and algorithms by:Creating datasets from our large data lake of products and social media data, selecting the most relevant items for your use case and ensuring data quality.Hands-on training, deploying, productionizing, and operating Machine Learning models and pipelines at scale, including both batch and real-time use cases.Contributing to expanding and improving the infrastructure to support all stages of the machine learning model lifecycle, including feature engineering, feature store, model training, testing, monitoring, and deployment in a production environment.Proactively identifying and implementing internal process improvements including automating manual work, optimizing data delivery, and redesigning infrastructure for greater scalability.Staying up-to-date with the latest industry trends and technologies to ensure our ML capabilities remain competitive and cutting-edge.Onboarding and enabling Data Scientists with varying levels of engineering expertise.Your Skills3+ years of experience as a software engineer.Bachelor's degree in Computer Science, Engineering, or related field.3+ years of experience as a production-level Python developer and familiarity with Deep Learning frameworks: TensorFlow, Keras, or Pytorch.Proficiency in machine learning and Python data libraries like scikit-learn, pandas, or numpy.Experience with Computer Vision



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