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

• 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
• Health Coverage - Health and wellness are important, that is why we have you and up to four family members in a premiere health plan. We have a couple of options, so you can choose what is best for you and your family
• Visual Benefit - Seeing your work for us would be a sight for sore eyes. We want your vision to always be at 100% which is why we offer up to $200.000 COP for any visual health expenses
• Life Insurance Plan - We have partnered with MetLife to offer a full-coverage Ife insurance plan. So, your family is covered, even if you are gone
• Medical Leave Coverage - We are one of the few companies that cover 100% of your medical leave, for up to 90 days. Your health is the most important thing to us
• Professional Growth Opportunities - We have designed a highly competitive and complete development process, where you will have all the tools to get where you have always wanted to be, personally and professionally
• Stock Option Purchase Plan - As an EPAMer you can be more than just an employee, you will also have the opportunity to purchase stock at a reduced price and become a part owner of our organization
• 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
• Community Benefit - You will be part of a worldwide community of over 50,000 employees, where you can learn, challenge yourself, stand out, and share your knowledge and experience with multicultural teams!