Position: Principle ML Engineer (Vertex AI GCP Kubeflow CI/CD Python BigData)
Location: 100% Remote (EST)
Duration: 12 Months Contract
Interview: Video
Must Have: Strong ML RAG LLM GenAI Vertex AI GCP Kubeflow CI/CD Python BigData
Job Description:
Identify new opportunities to improve business processes and improve consumer experiences and prototype solutions to demonstrate value with a crawl walk run mindset. Work with data scientists and analysts to create and deploy new product features on the ecommerce website instore portals and the Levis mobile app Implement endtoend 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 s 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. Establish scalable efficient automated processes for data analyses model development validation and implementation Write efficient and scalable software to ship products in an iterative continualrelease environment Contribute to and promote good software engineering practices across the team and build cloud native software for ML pipelines Contribute to and reuse community best practices Embody the values and passions that characterize Levi Strauss & Co. with empathy to engage with colleagues from multiple backgrounds
Example Projects:
Besides driving the transformation of Levis into a datadriven enterprise in general here are some specific projects you will work on and contribute to: Personalized insession product recommendation engine Customer Segmentation Automated text summarization and clustering NextBest offer prediction Design Micro assortments for NextGen stores Anomaly detection and Root Cause Analysis Unified consumer profile with probabilistic record linkage Visual search for similar and complementary products
About You:
- University or advanced degree in engineering computer science mathematics or a related field
- 7 years experience developing and deploying machine learning systems into production and independent contributor.
- Comfortable with Python ecosystem Visual Studio Code Jupyter Notebook.
- 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 objectoriented/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 MLflow Airflow TFX.
- Relevant working experience with Docker and Kubernetes is a big plus