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Added 14 mins ago
ES
Senior Data Engineer
Epsilon Solutions Ltd.
Mississauga, ON
- $65 to $70 CAD / hour
- Contract
We are seeking an experienced Senior Data Engineer with strong expertise in SQL, Data Warehousing, and Snowflake to join our Capital Markets technology team. The ideal candidate will play a…
Added 14 mins ago
MH
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- Full-time
Defined-benefit pension plan for long-term financial security.
Added 14 mins ago
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Site Reliability Engineer
Insight Global
Toronto, ON
- $60 to $70 CAD / hour
- Contract
Day 2 service operations readiness, including SRM, SLM, security management, problem management, incident management, capacity management, and billing/usage validation
Added 14 mins ago
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Senior Validation Engineer- Agentic AI
Sapphire Stream Technology
Toronto, ON · Greater Toronto Area, Canada
- Full-time
SST is seeking an experienced Senior Agentic AI – Validation & Automation Engineer to join our engineering team in Markham, Ontario.
Added 14 mins ago
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We are seeking a Senior Full-Stack Engineer to build and maintain a knowledge graph platform for enterprise data governance. The role involves developing scalable backend services,…
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Engineering Co-op Student - January 2027
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Princeton, BC
- $65,624 to $68,744 CAD / year
Reporting to the Senior Mine Engineer, Technical Services, the Engineering Co-op Student will apply their engineering knowledge to support both Engineering and Operations teams. As a member…
Added 44 mins ago
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Senior Data Engineer
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- Full-time
As Senior Data Engineer / Data Scientist, you will design, build, and operate the group's data ecosystem: integrating data from our core business systems, developing robust pipelines,…
Added 1 hour ago
IG
Tanium Engineer
Insight Global
Toronto, ON
- $55 to $70 CAD / hour
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Added 1 hour ago
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Lead Infrastructure Architect
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Toronto, ON · FSRA Head Office
- Full-time
Establishes and maintains cloud architecture governance, including resource standards, tagging conventions, cost controls, and security guardrails.
Added 1 hour ago
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Senior DevOps
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Remote, Canada
- Full-time
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Safe Software is looking for Senior DevOps to join our DevOps team. As a Senior DevOps engineer, you will lead the design and implementation of scalable CI/CD pipelines, develop and…
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RF Engineer
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We are seeking an RF Engineer to support the technical management, production readiness and lifecycle sustainment of an RF modem module used within a next-generation communications network.
Added 8 hours ago
G
Senior HPC and Platform Engineer
GeoSoftware
Calgary, AB
- Full-time
We are looking for an experienced HPC and platform engineer to join our Digital Platform team.
Added 8 hours ago
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S&P Global
Toronto, ON
- Full-time
…production support - maintaining accountability for quality, security, and performance at every…
Added 8 hours ago
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DevOps Engineer
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Toronto, ON
- Full-time
We are seeking a DevOps Engineer to build, maintain, and support modern DevOps platforms on Microsoft Azure, with a strong focus on AKS-based workloads, CI/CD automation, and cloud-native…
Added 9 hours ago
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DevOps Engineer
TD
Toronto, ON
- Full-time
We are seeking a DevOps Engineer to build, maintain, and support modern DevOps platforms on Microsoft Azure, with a strong focus on AKS-based workloads, CI/CD automation, and cloud-native…
Added 9 hours ago
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Senior Manager, Structural Engineer
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Ensure discipline technical work and team activities meet all health, safety, environmental, and security requirements.
Added 10 hours ago
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Manufacturing Engineer II
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Calgary, AB
- Full-time
The Manufacturing Engineer II plays a key role in supporting and optimizing sheet metal fabrication operations, with a strong focus on CNC programming, process improvement, and equipment…
Added 12 hours ago
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Systems Verification & Validation Engineer
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Mill Bay, BC
- $95,000 to $115,000 CAD / year
- Full-time
Systems Verification & Validation Engineer to join our specialized team. This role is responsible for designing, conducting, and reporting on IVVQ (Integration, Verification, Validation,…
Added 12 hours ago
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Senior Engineer, Cloud Operations
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- Full-time
Sleep Country Canada is looking for a Senior Cloud Engineer to plays a key role in ensuring the reliability, performance, and security of Sleep Country’s multi-cloud environment. This…
Added 12 hours ago
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Machine Learning Engineer
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Toronto, ON
- Full-time
We are now hiring a Machine Learning Engineer, based in Toronto.
Added 13 hours ago
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Ingénieur Manufacturier Senior - Réparation de composants / Senior Manufacturing Engineer - Componen
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Software Engineer – Full-Stack (React, TypeScript, Java)
S&P Global
Toronto, ON
- Full-time
…production support - maintaining accountability for quality, security, and performance at every…
Added 15 hours ago
Maintenance Person (with ticket) - Part Time
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Calgary, AB
Valid 5th Class Power Engineer Certificate required.
Added 16 hours ago
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Senior Network Engineer
Brunel
Canada
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Brunel has partnered with SB Energy to hire an Senior Network Engineer to support the development and execution of large-scale power generation and data center infrastructure projects…

GeoSoftware

Senior HPC and Platform Engineer

Calgary, AB, T2P 3C5, Canada

Full-time

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Job details

Job type: Full-time
Experience: Minimum 5 years of professional engineering experience in distributed computing, HPC or cloud platform engineering
Posting language: English
Posted: Nov 2, 2026

Original job description

About GeoSoftware

GeoSoftware is a global leader in Geoscience Software and provides a comprehensive range of software solutions that support our clients to achieve their goals. Our tools help our clients to develop a better understanding of the subsurface, manage exploration and development risks and quantify reserves more accurately with our advanced geoscience technology.

Working at GeoSoftware is all about passion and sharing our ambition for ongoing technological innovation. We have more than 150 employees, spread over 18 different countries. Our people are our most important asset and developing our talents is a priority. As part of GeoSoftware, you will work with international and diverse teams of experts in an environment of excellence which will enable you to create your own opportunities and realize your full potential.

Job Summary

We are looking for an experienced HPC and platform engineer to join our Digital Platform team.

You would own the execution layer of our next generation of geoscience software: the layer that takes a piece of scientific work and runs it, at the same scale and with the same result, across a range of compute environments. That range covers a single workstation, on-premise HPC under Slurm or PBS, managed services such as Databricks, cloud batch on AWS and Azure, and bring-your-own-cloud deployment into an externally administered subscription. You would also own the build and delivery pipeline that gets it there.

Breadth is the point of the role. The same work has to run across all of those backends behind one consistent interface, deploy securely into environments we do not administer, and perform well against blob storage rather than local disk.

You would work in a small, senior, distributed team alongside computational algorithm and front-end engineers.

Duties and Responsibilities

Distributed Execution

Design and build the distributed execution framework: task sequencing and dependencies, elastic scaling, checkpoint and restart, retry with backoff, structured error reporting and preservation of partial output
Make the same workload run across local multiprocessing, Dask, Ray, Slurm and PBS, managed Spark services such as Databricks, and the managed cloud batch services on Azure, AWS and GCP - behind one consistent interface, with a clear view of what each backend is actually good for
Design job submission, status, progress and cost reporting as structured, introspectable data, so that work can be launched and monitored programmatically and automatically as well as by hand, with guards that prevent a mistyped job from running for hours
Build the job admission, entitlement and metering path

Cloud and Deployment

Build and maintain infrastructure as code - Terraform in particular - that stands the platform up repeatably in bring-your-own-cloud and externally administered environments
Containerize compute components as lean, independently versioned images
Implement the security surface of a deployed system: identity and access management, least-privilege roles and service principals, secrets handling, network isolation, encryption in transit and at rest, and image and dependency scanning in the pipeline
Support restricted and disconnected deployment scenarios
Work with identity, blob and object storage, networking, quotas and cost control across at least one major cloud

Performance

Parallel decomposition and profiling of compute-bound scientific workloads, so that throughput demonstrably scales with available CPU, GPU and storage bandwidth
Diagnose and fix I/O-bound behaviour against blob and object storage: concurrency limits, throttling, request batching, and access patterns that are invisible on a local disk but cost minutes against a remote store
Establish and defend performance baselines, with measurement rather than assertion

Build, Release and Operations

Own CI/CD, build and release engineering: pipelines, a nightly regression harness, native installers for Windows and Linux, and containerized cloud delivery
Stand up observability: job lifecycle, resource utilization and cost visibility across every backend
Support what you build, and feed what you learn from doing so back into the design

Skills and Competencies

Skills:

Production experience with at least one distributed compute framework - Ray, Dask, Spark or MPI - and a clear view of where each is the right tool. Having run one at real scale and watched it fail is worth more than having read about all of them
Strong Python for orchestration, services and bindings
Solid modern C++, or the confidence to work in it: the compute kernels are native code and the binding seam is shared with the algorithm engineers
Infrastructure as code, Terraform in particular, and experience deploying the same system into environments you do not control
Containerization and Kubernetes, including image layering and size discipline
Working proficiency in one or two major cloud providers - Azure, AWS or GCP - with awareness of the others
Blob and object storage performance in practice, not only in principle
Practical cloud security: identity and access management, least-privilege roles, secrets management, network isolation and encryption
CI/CD pipelines, release engineering and the operational instincts that come from having supported what you built
Strong written English, and the habit of documenting asynchronously

Competencies:

Ownership and self-direction
Systems thinking across boundaries they do not personally own
Pragmatic judgement about where complexity is worth it
Collaboration across disciplines
Technical expertise (distributed computing and platform engineering)
Alignment with company interest

Qualifications & Requirements

Required:

Bachelor's degree in computer science, engineering, physics, mathematics or a related technical discipline, or equivalent practical experience
Minimum 5 years of professional engineering experience in distributed computing, HPC or cloud platform engineering
Demonstrable production experience with a distributed compute framework
Demonstrable experience with infrastructure as code, and working proficiency in one or two major cloud providers
Experience owning a CI/CD and release pipeline end to end
Sound security practice in cloud and containerized deployment: identity and access management, secrets handling and least privilege
Able to work effectively in a small, remote, multi-timezone team: writing things down, communicating asynchronously and operating without close supervision
Fluent written and spoken English

Desired:

HPC scheduler experience - Slurm or PBS - in a shared, contended environment
Managed cloud batch or Spark services: Databricks, Azure Batch or AWS Batch, and a view on when each beats a long-lived cluster
Oil and gas or seismic processing background, or other large-scale scientific computing
Cloud-native, chunked array storage formats and parallel I/O
OSDU, or other subsurface data platform integration
GPU computing: CUDA, or GPU-accelerated numerical libraries
Security certification or formal security review experience; supply-chain security, SBOM or vulnerability management
Restricted or disconnected deployment; software licensing and entitlement enforcement
Cost attribution and capping per job, per user and per tenant
Fluent with AI coding tools for prototyping, test generation and refactoring, with the judgement to know where their output must be verified rather than trusted

We value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.

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More about this job

Responsibilities

Design and build a distributed execution framework to run scientific workloads across various compute environments including local, on-premise HPC, and cloud platforms. Maintain infrastructure as code, manage CI/CD pipelines, and ensure performance and security across all deployed systems.

Requirements

Requires a bachelor's degree in a technical discipline and at least 5 years of professional experience in distributed computing, HPC, or cloud platform engineering. Candidates must demonstrate proficiency in infrastructure as code, cloud security practices, and distributed compute frameworks.

Skills

HPC
Distributed computing
Python
C++
Terraform
Kubernetes
Cloud computing
Azure
AWS
GCP
CI/CD
Containerization
Slurm
PBS
Dask
Ray

Visa sponsorship

Not detected in the job text

Keywords

HPC
Platform Engineering
Distributed Computing
Python
C++
Terraform
Kubernetes
Cloud Batch
Azure
AWS
GCP
CI/CD
Slurm
PBS
Dask
Ray
Spark
Databricks
Infrastructure as Code
Containerization
Identity and Access Management
Blob Storage
Object Storage
Performance Profiling
Geoscience Software
Release Engineering
Observability
Parallel Decomposition
Security
Automation

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