Senior Machine Learning Engineer

August 7

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Xebia Poland

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A place where experts grow.

Software Development • Agile Development • DevOps • Scrum • Mobile Applications

1001 - 5000

Description

• Working with teams of a globally recognized American apparel brand, symbol of rugged individuality and casual style • Identifying new opportunities to improve business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset • Working with data scientists and analysts to create and deploy new product features on the ecommerce website, in-store portals and the mobile app • Implementing end-to-end solutions across the full breadth of ML model development lifecycle • The specific role includes working hand in hand with the scientists from the point of data exploration for model development to the point of building features, ML pipelines and deploying them in production • You will have an opportunity to work on both batch and real time models • The role also involves operational support • Establishing scalable, efficient, automated processes for data analyses, model development, validation and implementation • Writing efficient and scalable software to ship products in an iterative, continual-release environment • Contributing to and promoting good software engineering practices across the team and build cloud native software for ML pipelines • Contributing to and re-using community best practices • Example Projects: Personalized in-session product recommendation engine, Customer Segmentation, Automated text summarization and clustering, Next-Best offer prediction, Design Micro assortments for Next-Gen stores, Anomaly detection and Root Cause Analysis, Unified consumer profile with probabilistic record linkage, Visual search for similar and complementary products

Requirements

• Ready to start immediately • University or advanced degree in engineering, computer science, mathematics, or a related field • 7+ years' experience in software development • Experience developing and deploying machine learning systems into production in a large data science environment • Able to operate as an independent contributor • Comfortable with Python ecosystem, vscode, jupyternotebooks • Experience working with big data tools: Hadoop, Spark, Kafka, etc. • Experience with at least one cloud provider solution (AWS, GCP) and understanding of serverless code development (GCP preferred) • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. (Python preferred) • CI/CD expert. And can work on GitHub actions, harness, Jenkins • Can work with Google Big Query, or similar warehouse • Work on Kubeflow pipelines independently and propose standards • Knowledge of Feature Engineering, Feature Store, and audit capabilities • Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation • Working experience with native ML orchestration systems such as Kubeflow, Step Functions, ML Flow, Airflow, TFX... • Relevant working experience with Docker and Kubernetes is a big plus • Strong reasoning to balance solution vs risk taking • Good verbal and written communication skills (English) • Cooperation with US west-coast based teams is part of the game – up to 2x in a week overlap with 9am PDT (18:00 CET) • Work from the European Union region and a work permit are required