Responsibilities

• Contribute to the refinement, establishment, and operational lifecycle of ML pipelines using industry best practices
• Design, create, maintain, troubleshoot, and enhance steps in ML pipelines
• Own and contribute to the design and execution of ML prediction endpoints
• Collaborate with System Engineers to establish an ML lifecycle management environment
• Draft specifications, documentation, and user guides for developed applications
• Support the enhancement of coding practices and organization of scientific work cycle repositories
• Set up pipelines for different projects
• Regularly identify technical risks and gaps and formulate risk mitigation strategies
• Collaborate with data scientists to transition predictive models into production, creating scalable data preparation pipelines, and understanding model scopes and purposes

Requirements

• Minimum of 3 years of experience as a Machine Learning Engineer or in a similar capacity
• Strong proficiency in programming languages, particularly Python
• Solid grasp of Data Science principles and Machine Learning Engineering model creation experience
• Expertise in Engineering Best Practices
• Comprehensive understanding of Machine Learning fundamentals
• Hands-on experience implementing Data Products using technologies like the Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML) or equivalent technologies
• Experience with Big Data technologies such as Hadoop, Spark, Kafka, Cassandra, GCP BigQuery, AWS Redshift, Apache Beam, etc
• Experience with automated data pipeline and workflow management tools like Airflow, Argo Workflow, etc
• Familiarity with different data processing paradigms (batch, micro-batch, streaming)
• Practical experience with one or more major Cloud Providers such as AWS, GCP, or Azure
• Experience with at least one MLOps-related platform/technology such as AWS SageMaker, Azure ML, GCP Vertex AI/AI Platform, Databricks MLOps-related tools/technologies like MLFlow, Kubeflow, TensorFlow Extended (TFX)
• Experience integrating ML models into complicated data-driven systems in a production environment
• Fluent in English with a B2+ level

Nice to have

• AWS, GCP, or Azure Certified would be a significant advantage
• Aptitude for rapidly adapting and applying new technologies
• Experience in a startup/environment, demonstrating the ability to deal with ambiguity

We offer

• 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