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!
We accept CVs in English only.

#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)

• 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!