SOLID.Jobs – Platforma rekrutacyjna dla specjalistów

PROJECT INFORMATION:

RESPONSIBILITIES:

Working with teams of a globally recognized American Apparel brand, the symbol of rugged individuality and casual style.
Identifying new opportunities to improve business processes and improving 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 e-commerce website, in-store portals, and the mobile app.
Implementing end-to-end solutions across the full breadth of the ML model development lifecycle. The specific role includes working hand in hand with the scientists from data exploration for model development to building features, and ML pipelines and deploying them in production. You will be able to work on 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.
Cooperation with US west-coast-based teams is part of the game – up to 2x a week overlap with 9 am PDT

REQUIREMENTS:

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 a 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, and TFX.
Relevant working experience with Docker and Kubernetes is a big plus.

Zdalnie

emagine to najwyższej klasy firma konsultingowa specjalizująca się w branży IT, outsourcingu i wsparciu biznesu.

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