Lead AI Platform Engineer

Hybrid in Mexico

Cloud Native Development

Location-specific conditions & benefits*

Mexico

We are seeking a highly skilled and motivated Lead AI Platform Engineer to join our cutting-edge team.

You will play a critical role in designing and deploying large-scale AI/ML infrastructure to solve transformative challenges in drug discovery and healthcare. This position offers the opportunity to develop state-of-the-art platforms and systems that empower data scientists, advancing global healthcare solutions and impacting millions of lives.

Responsibilities

Provide a robust infrastructure and platform to support the deployment and monitoring of machine learning solutions in production
Optimize solutions to ensure performance and scalability for large-scale systems
Collaborate with data science teams to develop cutting-edge AI/ML environments and workflows on AWS
Partner with R&D data scientists to productionize machine learning pipelines, models, and algorithms
Take ownership of all aspects of software engineering, including design, implementation, testing, and ongoing maintenance
Lead technology processes from concept development through to the successful delivery of projects
Enhance the technological stack to incorporate the latest advancements in data processing and artificial intelligence
Manage an enterprise-level platform and service, effectively addressing customer demands and feature requests
Introduce DevOps best practices and modern toolchains, driving automation and efficiency
Scale machine learning operations (MLOps) environments to production-grade standards
Ensure adherence to GxP standards where applicable

Requirements

5+ years of experience working with AWS cloud environments, including expertise in services like SageMaker, Athena, S3, EC2, RDS, Glue, Lambda, Step Functions, EKS, and ECS
Proficiency with infrastructure-as-code technologies such as Terraform, Ansible, or CloudFormation
Strong programming skills, particularly in Python, but other exceptional programming abilities will also be considered
Experience with containers, microservices architectures, and Kubernetes or Docker-based systems
Advanced understanding of Continuous Integration and Continuous Delivery pipelines, such as CodePipeline, CodeBuild, or CodeDeploy
Background in managing large-scale enterprise platforms and handling end-user interactions for new features and requests
Practical knowledge of DevOps practices and tools like Docker and Git
Familiarity with GxP compliance standards
Strong analytical, communication, and problem-solving abilities

Nice to have

Expertise in building large-scale data processing pipelines using technologies like Hadoop, Spark, or SQL
Skills in data science modeling tools and environments, e.g., R, Python, or Jupyter Notebooks
Familiarity with multi-cloud environments (e.g., AWS, Azure, and GCP)
Background in mentoring and supporting less experienced colleagues or clients in a professional setting
Experience applying SAFe Agile principles and practices

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