Responsibilities

• Contribution to the ML pipeline design, development, and operation based on industry best practices
• Designing, creating, maintaining, troubleshooting, and optimizing ML pipeline steps
• Taking ownership and contributing to the design and implementation of ML prediction endpoints
• Collaborating with System Engineers to configure the ML lifecycle management environment
• Writing specifications, documentation, and user guides for developed applications
• Supporting the improvement of coding practices and repository organization within the science work cycle
• Establishing and configuring pipelines for various projects
• Continuously identifying technical risks and gaps and formulating mitigation strategies
• Collaborating with data scientists to translate predictive models into production, understanding their scope and purpose, and creating scalable data preparation pipelines

Requirements

• A minimum of 5 years' experience with a programming language, preferably Python, along with a strong knowledge of SQL
• A proven history of leading and mentoring an engineering team
• Demonstrable MLOps experience (Sagemaker, Vertex, or Azure ML)
• Intermediate proficiency in Data Science, Data Engineering, and DevOps Engineering
• A record of at least one project delivered to production in an MLE role
• Expertise in Engineering Best Practices
• Practical experience implementing Data Products using Apache Spark Ecosystem (Spark SQL, MLlib/SparkML) or equivalent technologies
• Familiarity with Big Data technologies (e.g., Hadoop, Spark, Kafka, Cassandra, GCP BigQuery, AWS Redshift, Apache Beam, etc.)
• Proficiency with automated data pipeline and workflow management tools such as Airflow, Argo Workflow, etc
• Experience with different data processing paradigms (batch, micro-batch, streaming)
• Practical experience working with a major Cloud Provider such as AWS, GCP, and Azure
• Experience integrating ML models into complex data-driven systems
• DS experience with 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.)
• Fluency in English communication at a B2+ level

Nice to have

• Practical experience with Databricks MLOps-related tools/technologies like MLFlow, Kubeflow, TensorFlow Extended (TFX)
• Experience with performance testing tools such as JMeter or LoadRunner
• Knowledge 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