Responsibilities

• Involvement in the design, development, and operation of the ML pipeline in accordance with best practices
• Responsibility for the design, creation, maintenance, troubleshooting, and optimization of ML pipeline steps
• Participation in the design and implementation of ML prediction endpoints
• Cooperation with System Engineers to set up the ML lifecycle management environment
• Creation of specifications, documentation, and user guides for developed applications
• Assistance in improving coding practices and repository organization within the science work cycle
• Establishment and configuration of pipelines for projects
• Continuous identification and mitigation of technical risks and gaps
• Partnership with data scientists to move predictive models into production, understand the scope and purpose of the models, and create scalable data preparation pipelines

Requirements

• At least 5 years of experience in programming languages, ideally Python, coupled with a strong understanding of SQL
• A proven history of leading and mentoring a team of engineers
• Concrete MLOps experience (Sagemaker, Vertex, or Azure ML)
• Intermediate proficiency in Data Science, Data Engineering, and DevOps Engineering
• A history of at least one project delivered to production in an MLE role
• Expertise in Engineering Best Practices
• Hands-on experience in the implementation of Data Products using the Apache Spark Ecosystem (Spark SQL, MLlib/SparkML) or similar technologies
• Familiarity with Big Data technologies (e.g., Hadoop, Spark, Kafka, Cassandra, GCP BigQuery, AWS Redshift, Apache Beam, etc.)
• Proficiency in automated data pipeline and workflow management tools, such as Airflow, Argo Workflow, etc
• Experience in differing data processing paradigms (batch, micro-batch, streaming)
• Practical experience with at least one of the major Cloud Providers such as AWS, GCP, and Azure
• Production experience in the integration of ML models into complex data-driven systems
• DS experience with tools like Tensorflow/PyTorch/XGBoost, NumPy, SciPy, Scikit-learn, Pandas, Keras, Spacy, HuggingFace, Transformers
• Experience with various types of databases (Relational, NoSQL, Graph, Document, Columnar, Time Series, etc.)
• Fluent English communication skills at a B2+ level

Nice to have

• Hands-on experience with Databricks MLOps-related tools/technologies like MLFlow, Kubeflow, TensorFlow Extended (TFX)
• Familiarity with performance testing tools like JMeter or LoadRunner
• Understanding of containerization technologies like Docker

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