Back to SearchSenior Data DevOps Engineer
Colombia
We are seeking a highly skilled Senior Data DevOps Engineer to join our team and play an integral role in transforming cloud-based systems, optimizing costs, improving reliability, and enabling advanced analytics for the real estate industry. This is an opportunity to work with cutting-edge technologies in an environment that values innovation, automation, and scalability.
Responsibilities
- Manage and optimize the end-to-end lifecycle of machine learning systems
- Collaborate with business stakeholders to frame ML problems from business objectives
- Develop, implement, and maintain data solutions addressing ML challenges
- Design and build automated ML pipelines to streamline production workflows
- Orchestrate data preparation pipelines using tools like Kubeflow or Airflow
- Deploy ML models to production systems for real-time or batch applications
- Monitor ML models in production, ensuring optimal performance and reliability
- Leverage GCP tools such as Vertex AI and Vertex AI Pipelines to manage operations
- Automate infrastructure provisioning and deployment leveraging Terraform
- Optimize and improve system availability, cost efficiency, and deployment timelines
- Implement CI/CD pipelines for seamless deployment using tools like Jenkins
Requirements
- 3+ years of experience in designing, deploying, and maintaining ML systems in production
- Proficiency in Python with expertise in developing and automating ML workflows
- Expertise in cloud platforms with a focus on GCP tools such as Vertex AI and Vertex AI Pipelines
- Competency in infrastructure-as-code (IaC) using Terraform
- Experience with orchestration tools like Kubeflow or Airflow for data preparation pipelines
- Familiarity with CI/CD best practices and tools such as Jenkins
- Capability to monitor, optimize, and troubleshoot ML model performance in production
- Strong verbal and written communication skills in English, at least at a B2 level
Nice to have
- Experience in monitoring frameworks tailored for ML models
- Understanding of ML deployment paradigms and scalability best practices
- Showcase of successful production-grade ML model deployments at scale
- Background in working within highly data-driven industries like real estate or finance
- Flexibility to use advanced cloud-native tools for improved analytics and pipeline efficiency
We offer/Benefits
- International projects with top brands
- Work with global teams of highly skilled, diverse peers
- Healthcare benefits
- Employee financial programs
- Paid time off and sick leave
- Upskilling, reskilling and certification courses
- Unlimited access to the LinkedIn Learning library and 22,000+ courses
- Global career opportunities
- Volunteer and community involvement opportunities
- EPAM Employee Groups
- Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn