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
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