Design distributed execution with Python and Ray, Dask, Spark, or MPI for GeoSoftware’s geoscience platform across diverse compute environments.
As a Senior HPC and Platform Engineer, you will own execution, deployment, and delivery across workstations, HPC, managed services, and cloud batch. You will build consistent interfaces across Slurm, PBS, Databricks, AWS, Azure, and GCP. The work includes secure deployment, performance engineering, and platform operations for scientific workloads.
Key Responsibilities: Design task sequencing, scaling, checkpointing, retries, and structured error reporting
Run workloads across local, HPC, managed, and cloud backends
Build structured submission, monitoring, progress, cost, and entitlement paths
Implement Terraform, containers, security controls, and disconnected deployments
Own CI/CD,



releases, regression testing, and platform observability
Requirements: Minimum five years in distributed computing, HPC, or cloud platforms
Production experience with Ray, Dask, Spark, MPI, or another framework
Solid Python and solid modern C++ capability
Terraform, Kubernetes, containerization, and major cloud provider proficiency
Degree or equivalent experience, English fluency, and asynchronous remote collaboration
Bring distributed computing, Python, cloud security, and performance expertise to GeoSoftware’s execution platform for geoscience software.

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📌 Senior Distributed Computing Engineer (Alberta)
🏢 GeoSoftware
📍 Alberta