Lead AI Platform Engineer

Hybrid in Mexico

Cloud Native Development

Location-specific conditions & benefits*

Mexico

We are seeking a motivated and experienced Lead AI Platform Engineer to join our forward-thinking team.

In this role, you will play a key part in designing and deploying large-scale AI/ML infrastructure to tackle transformative challenges in healthcare and drug discovery. This is an exciting opportunity to build cutting-edge platforms and systems that empower data scientists, driving impactful healthcare solutions on a global scale.

Responsibilities

Develop and manage infrastructure and platforms to enable the deployment and monitoring of machine learning solutions in production
Enhance system performance and scalability for large-scale operations
Collaborate with data science teams to design advanced AI/ML workflows and environments on AWS
Work with R&D data scientists to operationalize machine learning pipelines, models, and algorithms
Take ownership of software engineering processes, including architecture, development, testing, and maintenance
Lead the development of technology initiatives from concept to successful delivery
Continuously upgrade the technology stack by incorporating advancements in artificial intelligence and data processing
Oversee an enterprise-level platform and service, addressing customer needs and feature requests effectively
Introduce and implement DevOps best practices and modern toolchains to improve automation and efficiency
Scale machine learning operations (MLOps) environments to production-grade standards
Ensure adherence to GxP compliance standards when required

Requirements

At least 5 years of experience working in AWS cloud environments, with expertise in services such as SageMaker, Athena, S3, EC2, RDS, Glue, Lambda, Step Functions, EKS, and ECS
Proficiency in infrastructure-as-code tools, including Terraform, Ansible, or CloudFormation
Strong programming skills, particularly in Python, with consideration for other programming expertise
Experience with containers, microservices architectures, and systems like Kubernetes or Docker
Advanced understanding of Continuous Integration and Continuous Delivery pipelines, including tools like CodePipeline, CodeBuild, or CodeDeploy
Proven experience managing large-scale enterprise platforms and addressing end-user feature requests
Hands-on experience with DevOps practices and tools, including Docker and Git
Familiarity with GxP compliance standards
Strong analytical, problem-solving, and communication skills

Nice to have

Experience developing large-scale data processing pipelines with technologies like Hadoop, Spark, or SQL
Proficiency in data science modeling tools and platforms, such as R, Python, or Jupyter Notebooks
Knowledge of multi-cloud environments, including AWS, Azure, and GCP
Experience mentoring and supporting team members or clients in a professional setting
Familiarity with SAFe Agile frameworks and methodologies

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