We are seeking a Senior Machine Learning Engineer to join our remote team. This role involves contributing to the design, development, and operation of ML pipelines based on best practices.

You will be responsible for designing, creating, maintaining, troubleshooting, and optimizing steps within the ML pipeline, as well as owning and contributing to the design and implementation of ML prediction endpoints. Collaborating with System Engineers to configure the ML lifecycle management environment and supporting the improvement of coding practices will be key aspects of your role.

If you are passionate about innovation, we invite you to apply and become part of our team!

#LI-DNI

• Contribute to the design, development, and operation of the ML pipeline based on best practices
• Design, create, maintain, troubleshoot, and optimize steps in the ML pipeline
• Own and contribute to the design and implementation of ML prediction endpoints
• Collaborate with System Engineers to configure the ML lifecycle management environment
• Write specifications, documentation, and user guides for developed applications
• Support the improvement of coding practices and organization within the science work cycle
• Establish and configure pipelines for projects
• Identify technical risks and gaps continuously, and devise mitigation strategies
• Collaborate with data scientists to productionalize predictive models, understanding the scope and purpose of models, and creating scalable data preparation pipelines

• 3+ years of Python programming experience with strong SQL knowledge
• Strong MLOps experience (e.g., Sagemaker, Vertex, Azure ML)
• Intermediate level in Data Science, Data Engineering, and DevOps Engineering
• Experience with at least one project delivered to production in an MLE role
• Experience with the Apache Spark Ecosystem (e.g., Spark SQL, MLlib/SparkML)
• Experience with automated data pipeline and workflow management tools (e.g., Airflow)
• Experience in different data processing paradigms (batch, micro-batch, streaming)
• Practical experience working with at least one of the major Cloud Providers (AWS, GCP, Azure)
• Production experience in integrating ML models into complex data-driven systems

• Practical experience with Databricks MLOps-related tools (e.g., MLFlow, Kubeflow)
• Experience with performance testing tools (e.g., JMeter)
• Knowledge of containerization technologies (e.g., Docker)

• Improved medical coverage - EPAMers are eligible to participate in a supplementary health insurance program that shall have the usual coverage in the industry, with the Company funding 100% of the value of the monthly premium for participation
• Lunch Allowance - You will receive a daily allowance of CLP $ 7.000 per working day. Enjoy a nice meal on us
• Allowance for internet and electricity - You will receive an allowance of CLP$15.000 per month to cover internet and electricity expense
• National Holiday Bonus - We celebrate joining the Chilean Market. That is why all our employees will receive a bonus of CLP $86,646 in September
• Christmas Bonus - You will receive an End of Year bonus of CLP $170,539. It will be paid during the month of December, to ensure you have a Happy Holiday!
• Learning Culture - We want you to be the best version of yourself, that is why we offer unlimited access to learning platforms, a wide range of internal courses, and all the knowledge you need to grow professionally
• Additional Income - Besides your regular salary, you will also have the chance to earn extra income by referring talent, being a technical interviewer, and many more ways
• Are you open to relocation? - If you want to relocate to another country and we have the right project, we will assist you every step of the way, to help you and your family, reach your new home