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

Strong Python and solid contemporary 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.

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