Platform Engineer (Machine Learning)
Seeking a strong Platform Engineer to help design and operate cloud platforms machine learning infrastructure evaluation systems and developer environments. The primary focus of this role is building a machine learning competition and evaluation platform where participants submit ML projects that are executed and scored in secure GPU-enabled runtime environments. This role sits at the intersection of cloud infrastructure developer platforms automation ML/GPU compute and distributed systems. You will work on projects such as ML competition and evaluation platforms GPU-based compute environments Dockerized and sandboxed runtime environments secure multi-tenant cloud infrastructure model evaluation and benchmarking systems infrastructure automation and provisioning internal developer tooling and orchestration systems and CI/CD and deployment automation. There may also be opportunities to contribute to internal R&D around AI inference and LLM infrastructure.
Key Responsibilities:
- Design and maintain cloud infrastructure primarily on AWS.
- Build reusable platform tooling and automation systems used by other engineers.
- Provision and manage infrastructure using Terraform/OpenTofu.
- Configure and maintain Docker-based environments and containerized workloads.
- Develop Python automation and orchestration scripts.
- Build and operate GPU-enabled compute environments for machine learning workloads including sandboxed runtime environments for user-submitted code.
- Build and improve CI/CD workflows for efficient software delivery.
- Monitor troubleshoot and optimize infrastructure reliability and performance.
- Improve developer workflows internal tooling and platform usability.
- Contribute to architecture and operational decisions across projects.
- Ensure security best practices are followed throughout the platform lifecycle.
- Stay up-to-date with the latest cloud ML infrastructure and platform engineering trends.
Job Experience and Skills Required:
- Bachelors degree in Computer Science Engineering Information Systems or a related field (or equivalent practical experience).
- 5 years of hands-on experience operating production cloud infrastructure (mid to senior level).
- Strong experience with Linux systems administration.
- Strong experience with Docker and containerized environments.
- Strong experience with AWS or similar cloud platforms.
- Strong experience with Terraform or other infrastructure-as-code tooling.
- Proficiency in Python scripting and automation.
- Proficiency with Git and GitHub workflows.
Apply now!
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For more information contact:
Lameez Mohamed
Specialist Recruitment Consultant
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