MLOps and Data Engineer - El Salvador
Xe, El Salvador
Job Description
PLEASE READ: If you are interested in applying to the role, we ask that you kindly complete the application in English and attach an English version of your resume. Thank you.
At XE, we live currencies. We provide a comprehensive range of currency services and products, including our Currency Converter, Market Analysis, Currency Data API and quick, easy, secure Money Transfers for individuals and businesses. We leverage technology to deliver these services through our website, mobile apps and over the phone. At XE, we share the belief that behind every currency exchange, query or transaction is a person or business trying to accomplish something important, so we work together to develop new and better currency services that put our customers first. We are proud to be part of Euronet Worldwide (Nasdaq: EEFT), a global leader in processing secure electronic financial transactions. Under Euronet, we have brought together our key brands XE, HiFX and Currency Online to become the business that XE is today.
XE is looking for an experienced MLOps and data Engineer to join the XE Data Science team. As a MLOps and Data Engineer you’ll be responsible for designing, building, and maintaining the infrastructure and processes required to successfully deploy and manage machine learning models in a production environment. This includes tasks such as building and maintaining feature store, delivery pipelines, automating model training and evaluation, and monitoring model performance.
The MLOps and Data Engineer will work closely with data scientists and software engineers to ensure that machine learning models can be seamlessly integrated into existing systems and processes. They will also be responsible for identifying and implementing best practices for managing and optimizing machine learning models in production.
The ideal candidate for this role will have strong experience in both software engineering and machine learning, as well as a deep understanding of the challenges and best practices involved in deploying machine learning models in production. Having experience working with cloud computing platforms such as AWS or GCP is a plus.
Responsibilities
- Build and maintain real-time machine learning features using production level programming techniques
- Design, Develop, and maintain a central feature store
- Automate the training, evaluation, and deployment of machine learning models
- Monitor and optimize the performance of machine learning models in production
- Work closely with data scientists and software engineers to ensure the successful integration of machine learning models into existing systems and processes
- Identify and implement best practices for managing and optimizing machine learning models in production
Requirements
- Degree in Computer Science, Software Engineering, or related discipline
- Strong knowledge of developing and maintaining API services in a cloud environment
- Strong OO and SO programming skills in Python to write effective, scalable codes.
- Knowledge of modern containerization techniques - Docker, Docker Compose
- Experience with relational and unstructured databases and data lakes
- An understanding of business goals and how data policies can affect them
- Effective communication and collaboration skills
- A strong understanding of the concepts associated with privacy and data security
Benefits
Life insurance
Shared medical insurance
Tuition Assistance
English classes