Back to SearchSenior AI Platform Engineer with AWS Expertise
Hybrid in Mexico
Data DevOps
& 9 others
We are looking for a Senior AI Platform Engineer to deliver robust infrastructure supporting production ML solutions on AWS, enhancing AI/ML workflows and platforms.
You will collaborate with data science teams to architect innovative AI/ML environments using AWS services like SageMaker and EKS, driving projects from inception to delivery. Join us to advance AI technology within a forward-thinking team.
Responsibilities
- Deliver infrastructure and platforms to enable deployment and monitoring of ML solutions in production
- Improve ML solution performance and scalability on AWS
- Work closely with data science teams to build AI/ML workflows and environments leveraging AWS services
- Coordinate with R&D data scientists to operationalize ML pipelines, models, and algorithms
- Own software engineering lifecycle from design through implementation, testing, and maintenance
- Drive technology initiatives from initial concept through to project completion
- Collaborate with cross-functional teams to integrate advances in Data Processing and AI into the technology stack
Requirements
- Extensive experience working with AWS cloud infrastructure, including 3+ years in DevOps or related roles
- Proficient knowledge of AWS services such as SageMaker, Athena, S3, EC2, RDS, Glue, Lambda, Step Functions, EKS, and ECS
- Hands-on experience with DevOps tools including Docker and Git
- Strong skills in infrastructure as code using Terraform, Ansible, and CloudFormation
- Advanced programming ability in Python
- Background managing enterprise platforms and responding to client demands and feature requests
- Experience with containerization and microservices architectures like Kubernetes, Docker, and serverless systems
- Proven experience with CI/CD pipelines including CodePipeline, CodeBuild, and CodeDeploy
- Familiarity with GxP compliance standards
- Excellent communication, analytical thinking, and problem-solving capabilities
- English proficiency at Upper-Intermediate (B2) level
Nice to have
- AWS or related cloud technology certifications
- Familiarity with large-scale data processing frameworks such as Hadoop or Spark
- Experience using data science tools like R and Jupyter notebooks
- Exposure to multi-cloud environments including AWS, Azure, or GCP
- Skills in mentoring, coaching, and supporting peers and clients
- Understanding of SAFe agile methodologies
- Practical experience building MLOps environments ready for production