We are seeking a Lead Machine Learning Engineer to join our remote team and assist in the design, development, and operation of ML pipelines based on best practices.

In this role, you will be responsible for designing, creating, maintaining, troubleshooting, and optimizing steps in ML pipelines. You will also lead and contribute to the design and implementation of ML prediction endpoints. Your role will also involve collaborating with System Engineers to configure environments for ML lifecycle management and improve coding practices.

If you are passionate about innovation, we invite you to apply and join our team!

#LI-DNI

Responsibilities

• Contribution to ML pipeline design, development, and operating lifecycle
• Design, creation, maintenance, troubleshooting, and optimization of ML pipeline steps
• Ownership and contribution to ML prediction endpoints design and implementation
• Collaboration with System Engineers to configure ML lifecycle management environment
• Writing specifications, documentation, and user guides for developed applications
• Support in improving coding practices and repository organization
• Establishing and configuring pipelines for projects
• Continuous identification of technical risks and gaps with strategies for mitigation
• Collaboration with data scientists to productionalize predictive models and create scalable data preparation pipelines

• 5+ years of Python programming experience with strong SQL knowledge
• 1+ years of relevant leadership experience
• Strong MLOps experience (e.g., Sagemaker, Vertex, Azure ML)
• Intermediate level in Data Science, Data Engineering, and DevOps Engineering
• Track record of delivering at least one project to production in an MLE role
• Background in the Apache Spark Ecosystem (e.g., Spark SQL, MLlib/SparkML)
• Proficiency in automated data pipeline and workflow management tools (e.g., Airflow)
• Experience in different data processing paradigms (batch, micro-batch, streaming)
• Practical experience with at least one major Cloud Provider (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