Job Description:

Design, code, train, test, deploy, and iterate on large-scale, distributed machine learning systems. Collaborate with a multi-functional agile team of data science, UX / UI design, product management, and engineering to build new features / products /services that delight our customers. Work with data scientists and data engineers to create end-to-end machine learning feedback loop and integrate it into various applications. Improve existing machine learning models both in terms of model performance and computing performance. Help drive code review, optimization, testing, and tooling to improve code quality and system reliability. Research and implement best practices to enhance existing machine learning infrastructure and process. Be part of an active group of data science and machine Learning practitioners that shape the direction of machine learning and artificial intelligence of the organization.

Qualifications:

BS (or higher, e.g., MS, or PhD) in Computer Science, Computer Engineering orrelated technical fields involving Machine Learning or equivalent technical experience Strong analytical and problem-solving skills - Proven software development skills in multiple programming languages (e.g., Python, Golang, C++) Experience with machine learning software packages (e.g., scikit-learn, XGBoost, TensorFlow, Caffe, Theano, Torch) Familiarity with container-based technologies (e.g., Docker, Kubernetes) and DevOps practices (e.g., code review, automated testing, CI / CD, logging, performance monitoring) Strong communication skills & collaborative mindset Experience with data processing tools (e.g., Hadoop, Apache Spark, Apache Beam) and Cloud platforms (e.g., AWS, Azure, GCP) considered a plus