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Added 15 days ago
Senior Data Analyst
Konrad
Toronto, ON
Proficiency in Python, R, or similar language for data analysis and automation
Added 15 days ago
EV
May 2027 Geographic Information Systems (GIS) Co-op
Elk Valley Resources
Calgary, AB
- $4,275 to $6,167 CAD / month
- Full-time
Familiarity with FME and AutoCAD as well as programming skills in in Python, Arcade, and SQL are an asset
Added 15 days ago
CS
AI & Automation Solutions Specialist
CAA Saskatchewan
Regina, SK
- Full-time
We are seeking an innovative AI & Automation Solutions Specialist to help advance AI and automation across CAA Saskatchewan. Working with teams throughout the organization, you’ll identify…
Added 15 days ago
O
Cloud Network Architect
OnX
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Automation and Infrastructure as Code for networking: Terraform (modules/state), Ansible, and scripting (e.g., Python) with Git-based workflows and CI/CD pipelines for repeatable…
Added 15 days ago
A
ASIC Verification Engineer, AI Networking IP
AMD
Ottawa, ON · Kanata, ON
- $91,200 to $136,800 CAD / year
- Full-time
Experience with Python, Perl or other scripting languages is an asset
Added 15 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking an experienced Python Developer with 8+ years of experience to develop backend services, analyze data flows and source code, and build reliable software solutions. The ideal…
Added 15 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking an experienced Python Developer with 8+ years of experience to develop backend services, analyze data flows and source code, and build reliable software solutions. The ideal…
Added 15 days ago
SM
Python Developer - Hybrid
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking an experienced Python Developer with 8+ years of experience to develop backend services, analyze data flows and source code, and build reliable software solutions. The ideal…
Added 15 days ago
A
AI/ML Systems Engineer
Actalent
Ottawa, ON
- $55 to $79 CAD / hour
- Contract
Proficiency in Python for automation, data processing, and application functionality.
Added 15 days ago
AC
Revenue Management Analysis, Science and Innovation Analyst
Air Canada
Dorval, QC
- Full-time
Technology skills in particular working with large databases (SQL or Dataiku), coding (R and Python preferred), reporting tools (PowerBI, Tableau or Fabric) and agentic flow design (such as…
Added 15 days ago
A
AI/ML Systems Engineer
Actalent
Ottawa, ON
- $55 to $79 CAD / hour
- Contract
Proficiency in Python for automation, data processing, and application functionality.
Added 15 days ago
A
Software Engineer
Actalent
Ottawa, ON
- $50 to $74 CAD / hour
- Contract
Experience with Python scripting at a mid level, particularly for automation and testing.
Added 15 days ago
A
Senior Test Engineer
Actalent
Ottawa, ON
- $50 to $60 CAD / hour
- Contract
Proficiency with Python for scripting and programming in test environments.
Added 15 days ago
E
SW Developer
Ericsson
Ottawa, ON
- Full-time
Experience with Linux and Python or Bash scripting.
Added 15 days ago
C
Software Developer Embedded Systems I (Co-op) - Canada
Cisco
AB · Ottawa, ON · Toronto, ON · Montreal, QC · Kanata, Ontario · Calgary, Alberta · Saint-Laurent, Quebec
- Full-time
As an Embedded Systems Software Developer Co-op, you will contribute to the design, enhancement, and testing of foundational software powering Cisco’s networking platforms and intelligent…
Added 15 days ago
Sr. Software Development Engineer in Test, AI/ML
PlayStation Global
Waterloo, ON
We are hiring a Sr Software Engineer in Test specializing in ML/AI quality, including automation for model evaluation, LLM-assisted test generation, and validation of AI-powered workflows.…
Added 15 days ago
C
Software Developer Embedded Systems I (Co-op) - Canada
Cisco
Toronto, ON
- Full-time
As an Embedded Systems Software Developer Co-op, you will contribute to the design, enhancement, and testing of foundational software powering Cisco’s networking platforms and intelligent…
Added 15 days ago
AE
Senior Engineer/Analyst
Alberta Electric System Operator (AESO)
Calgary, AB
- Full-time
Advanced proficiency in Python, with experience developing complex analytical applications and automation solutions
Added 15 days ago
KG
Principal Hydrogeologist
Kinross Gold Corporation
Toronto, ON
- Full-time
Founded in 1993, Kinross is a Canadian-based senior gold mining company with operations and projects in the United States, Brazil, Mauritania, Chile and Canada. Our focus on delivering…
Added 15 days ago
Physical Design Engineering Director
Astera Labs
Toronto, ON
…through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera…
Added 15 days ago
SS
Head of R&D
Seller Snap, Inc.
Brampton, ON · Regional Municipality of Peel, ON
- Full-time
Lead adoption of AI-assisted development across R&D, finding the right balance between automation and human checks, with guardrails around what AI can and can't touch.
Added 15 days ago
RB
Lead Full Stack Developer
Royal Bank of Canada
Toronto, ON
- Full-time
Coding experience in Python; including experience with libraries such as Pandas or NumPy for data manipulation and visualization.
Added 15 days ago
Principal Software Engineer
Conga
Canada
Lead development in an Agile, CI/CD environment with a strong emphasis on automation, testability, and observability.
Added 15 days ago
C
AI Inference Core - Technical Lead Manager, Release Qual & Integration
Cerebras
Toronto, ON
- Full-time
Partner with and mentor SDETs, feature teams, Integration, Core Infra, release owners, and deployment teams; between active engagements, advance automation efficiency, diagnostics, probes,…
Added 15 days ago
S
Operational Developer
Sherweb
QC
- Full-time
As an Operational Developer, you will help improve the delivery of our IT solutions by contributing to the implementation, maintenance, and continuous enhancement of our tools and…

Cerebras

AI Inference Core - Technical Lead Manager, Release Qual & Integration

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 22, 2026
Posting language: English
Posted: Oct 23, 2026

Original job description

About the Role

We are looking for a hands-on Technical Lead Manager (Release Qual & Integration) to establish and lead Release Integration Testing within Release & Feature Qualification for AI Inference Core.

The Production Engine for Inference Core - turning integrated features into reliable production releases.

You will define the quality strategy across the pre-release and release cycle, from feature and model integration through branch stability, release qualification, deployment, and post-release learning. You will work across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware to make release risk visible and actionable.

This is a technical-leadership role, not a coordination-only position. You will design test architecture, lead difficult debugging and release decisions, mentor engineers, and write software and automation alongside the team.

Release Integration Testing (RIT) is the bridge between feature qualification and release qualification. Feature teams retain ownership of feature design, feature-level qualification, and feature regression. Release Integration Testing owns inference-core integration strategy, inference-path readiness approval, integrated cross-stack validation, and first-pass rollout triage.

What Makes This Role Distinct

Dedicated Release Integration Testing ownership: Engage before feature qualification completes while keeping the boundary clear: feature teams own feature behavior and qualification; Release Integration Testing owns integration strategy, readiness approval, integrated validation, and first-pass rollout triage.
Inference-path readiness gate: Require evidence across unit, simulation, benchmark, feature, and integration testing, with explicit coverage gaps before release entry.
Cross-stack test strategy: Define risk-based E2E and regression coverage for features spanning components, organizations, software layers, infrastructure, and hardware.
Branch and rollout leadership: Establish measurable health standards for master and release branches, and coordinate inference-impacting rollout across multiple product and release projects.
Hands-on technical authority: Lead through code, test architecture, difficult debugging, quality metrics, and evidence-based release decisions.
Team multiplier: Raise the technical bar, mentor engineers, and align feature, infrastructure, integration, qualification, and release teams.

What You Will Do

Define the Release Integration Testing strategy, engagement criteria, ownership boundaries, entry and exit criteria, coverage expectations, and escalation thresholds for AI Inference Core.
Engage early on high-risk inference changes; identify dependencies and interaction risks across runtime, host, device programming, memory, scheduling, model execution, infrastructure, and hardware.
Own the inference-path readiness gate by reviewing unit, simulation, benchmark, feature-test, and integration evidence, documenting gaps, and approving integration readiness before release entry.
Lead integrated inference E2E validation across features and the cloud-to-wafer stack; promote durable feature tests and add risk-based scenarios to release regression.
Improve master and release-branch stability through actionable health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines.
Lead first-pass regression and rollout triage, coordinate owners through resolution, drive RCA, place missing coverage at the correct layer, and plan rollout across multiple product and release projects.
Partner with and mentor SDETs, feature teams, Integration, Core Infra, release owners, and deployment teams; between active engagements, advance automation efficiency, diagnostics, probes, and roadmap test planning.

Minimum Skills & Qualifications

Strong software-engineering fundamentals and programming ability in Python Go, or a similar language.
Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration.
Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software.
Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution.
Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics.
Ability to influence and align multiple engineering teams without relying solely on organizational authority.
Clear communication and sound judgment during high-pressure release situations, including the ability to explain technical risk to engineering and leadership audiences.

Preferred Skills

Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.
Experience with AI infrastructure, model deployment, LLMs, multimodal workloads, or large-scale compute clusters.
Experience building test frameworks, distributed test systems, release pipelines, dashboards, or internal developer tooling.
Experience with performance testing, profiling, observability, fault injection, reliability, or production failure analysis.
Experience managing geographically distributed teams across multiple regions and time zones is preferred
Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
Track record of taking a quality or release capability from zero to one and scaling it across teams.
Familiarity with containers, cluster orchestration, cloud infrastructure, CI/CD, or high-performance computing.

What Success Looks Like

Release readiness is based on explicit criteria and high-signal evidence rather than intuition.
Fewer inference-path integration defects are first discovered in final release qualification or production.
Cross-component risks are found earlier, debug cycles are shorter, and coverage ownership is explicit.
Master and release-branch health is measurable, actionable, and steadily improving.
Test automation and release infrastructure shorten feedback loops without sacrificing signal quality.
Release metrics and reports drive clear decisions, ownership, and predictable feature rollout.
Engineers across the organization are more effective because Release Integration Testing provides strong technical direction, tooling, and mentorship.

Location

This role requires in-office presence, at least three days per week. Fully remote work is not available.
Office locations: Sunnyvale, CA or Toronto, ON.

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More about this job

Responsibilities

Establish and lead Release Integration Testing for AI Inference Core, defining cross-stack test strategy, readiness criteria, and evidence-based release decisions. Lead integrated validation, branch health improvements, regression and rollout triage, and cross-team technical direction while mentoring engineers and advancing test automation.

Requirements

Candidates need strong software engineering and programming ability in Python, Go, or a similar language, plus technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex integration. They must be able to design automation for distributed or systems-level software, investigate ambiguous cross-stack failures, apply risk-based release practices, and influence multiple engineering teams.

Skills

Python
Go
Software Engineering
Release Integration Testing
Test Architecture
Distributed Systems Validation
Risk-Based Testing
Release Readiness
Regression Testing
Failure Analysis
Root Cause Analysis
Quality Metrics
AI Infrastructure
Performance Testing
CI/CD
Technical Leadership

Visa sponsorship

Not detected in the job text

Keywords

AI Inference Core
Release Integration Testing
Release Qualification
Inference Path Readiness
Python
Go
AI Frameworks
Runtime
Compiler
Kernels
Distributed Systems
Infrastructure
Hardware Accelerators
Model Deployment
LLMs
Multimodal Workloads
Test Automation
End-to-End Testing
Regression Testing
Release Engineering
Branch Stability
Performance Testing
Profiling
Observability
Fault Injection
Root Cause Analysis
Containers
Cluster Orchestration
Cloud Infrastructure
CI/CD

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