ML Engineer

Global Apps Inc
Global Apps Inc

Job Overview

Role ML Engineer Location San Francisco, CA Responsibilities Architect, build, maintain, and improve new and existing suite of algorithms and their underlying systems. Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance testing and AB testing Utilize your entrepreneurial spirit to identify new opportunities to optimize business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset. Work closely with data scientists and analysts to create and deploy new product features on the ecommerce website, in-store portals and the Levirsquos mobile app Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation Write efficient and well-organized software to ship products in an iterative, continual-release environment Contribute to and promote good software engineering practices across the team Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code Communicate clearly and effectively to technical and non-technical audiences equally well Actively contribute to and re-use community best practices Embody the values and passions that characterize Levi Strauss Co., with empathy to engage with colleagues from a wide range of backgrounds MUST have experience Model pipeline deployment Mode lifecycle management Productionize models Model automation Model scoring Minimum Qualifications 5+ years experience developing and deploying machine learning systems into production Strong experience working with a variety of relational SQL and NoSQL databases Strong experience working with big data tools Hadoop, Spark, Kafka, Scikit-learn, Tensorflow, Keras, Pytorch, Spark MLLIB etc. Experience with at least one cloud provider solution (AWS, GCP, Azure) Strong experience with object-orientedobject function scripting languages Python, Java, C++, Scala, etc. Experience with Platforms like H2O, Sage maker, MLFlow, Anaconda etc. Experience with framework like Scikit-learn, Tensorflow, Keras, Pytorch, Spark MLLIB etc. Ability to work in a Linux environment Industry experience building and productionizing innovative end-to-end Machine Learning systems Ability to quickly prototype ideas and solve complex problems by adapting creative approaches Experience working with distributed systems, service oriented architectures and designing APIs Strong knowledge of data pipeline and workflow management tools Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation Relevant working experience with Docker and Kubernetes is a big plusML Engineer 1

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