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We are seeking a seasoned expert to fill the role of MLOps Platform Engineer.
This individual will serve as a Senior consultant embedded with our clients, transforming their ML infrastructure operations. The successful candidate will combine deep platform engineering expertise with client-focused delivery, working closely with other team members and client engineering teams to build and optimize foundational ML infrastructure.
The responsibilities of this role include:
- Designing and implementing large-scale build systems supporting complex ML model training and deployment pipelines.
- Developing HPC integration solutions utilizing the Slurm REST API for cloud-native ML workloads on Google Cloud Platform (GCP).
- Optimizing performance for containerized workloads, including large containers and long-running machine learning (ML) processes.
- Implementing client infrastructure using Terraform on GCP, integrating with existing Vertex AI and GKE environments.
- Leading client infrastructure migration initiatives from Azure DevOps to GitHub Actions, working within client timelines and constraints.
The ideal candidate will have a proven track record in consulting environments and strong expertise in GCP infrastructure and Vertex AI platform deployment. They should also be proficient in Python backend services development and optimization techniques, as well as hands-on experience with Kubernetes orchestration and GKE in enterprise environments.
We value a candidate who is able to communicate effectively with clients and stakeholders, has strong technical skills, and can work independently within client environments.
Please note that we are looking for someone who is passionate about delivering high-quality solutions and has a keen eye for detail.
