Machine Learning Engineer (ML Ops)

-About: We are bringing KBTG technology to create financial innovations, and we are looking for the brightest minds in the business to help us. Together with our best-in-class, multidisciplinary people, you will be working with cross-functional teams to create innovations that improve customer’s quality of life in both financial and non-financial world. If you have the passion, grit, and curiosity to build innovative products from the ground up, we invite you to join our squad.  

JOB DESCRIPTION / RESPONSIBILITIES: 

• 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 or related 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