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Added 12 mins ago
Senior Data Engineer
HOOPP (Healthcare of Ontario Pension Plan)
Toronto, ON
$103,000 to $153,000 CAD / year
Full-time
Our Enterprise Data Platform team builds and operates the cloud data platform that powers analytics, reporting, and AI across HOOPP. As a Senior Data Engineer, reporting to the Senior…
Added 12 mins ago
Senior Data Solutions Engineer
HOOPP (Healthcare of Ontario Pension Plan)
Toronto, ON
$103,000 to $153,000 CAD / year
Full-time
…future for the healthcare community. As a Senior Data Solution Engineer, you will help keep HOOPP's investment data ecosystem reliable, governed, and ready to evolve toward a shared…
Added 12 mins ago
Azure DevOps engineer
IFG - International Financial Group
Vancouver, BC · Greater Vancouver, BC
Contract
Title: DevOps Engineer – Azure DevOps, CI/CD & Agentic AI
Added 12 mins ago
Mechanical Design Engineer - Robotic Hand
Humanoid
Burnaby, BC
Full-time
…mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even…
Added 12 mins ago
IBM Financial Transaction Manager (FTM) Engineer
K&K Global Talent Solutions INC.
Toronto, ON
Full-time
Experienced IBM Financial Transaction Manager (FTM) Engineer responsible for designing, developing, and supporting payment processing applications built on IBM FTM. Expertise in payment…
Added 28 mins ago
Senior DevOps Engineer
Boeing
Richmond, BC · Vancouver, BC · CAN - Richmond, Canada
Full-time
The ideal senior DevOps engineer is a cloud‑native platform expert with deep Azure Functions, CI/CD, IaC, and observability skills, plus strong leadership and cross‑team collaboration…
Added 43 mins ago
Director, Data Engineering, International Banking, Toronto, Mexico, Colombia, Peru
Scotiabank
Toronto, ON
…security, scalability, and cost efficiency of the Azure Databricks platform and related data operations across Mexico, Caribbean, Chile, Peru, and…
Added 56 mins ago
Senior Platform Engineer – RPA & Automation : Toronto, ON : Hybrid : Full time
AceStack
Toronto, ON
Full-time
Role: Senior Platform Engineer – RPA & Automation
Added 56 mins ago
Production Support - Elite Quant Fund- Up to $180,000 CAD + Bonus
Hunter Bond
Montreal, QC
Full-time
My client is hiring a Production Support Engineer to support mission-critical front office trading systems in a fast-paced, high-performance environment where uptime, speed, and reliability…
Added 56 mins ago
Cloud Engineer - Early Career (Canada)
Jobright.ai
Canada
Full-time
Jobright is your personal AI job search agent that transforms the way you do job search. They are seeking a Cloud Engineer to provision and manage cloud infrastructure, build CI/CD…
Added 56 mins ago
Data Engineer
Experis
ON · Ontario, Canada
$40 to $51 CAD / hour
Contract
We are seeking a Data Engineer to join a collaborative Agile team focused on building scalable data solutions that power analytics and AI-driven initiatives. This is an exciting opportunity…
Added 56 mins ago
Software Engineer – Elite Quant - Up to $200,000 CAD Starting base + Exceptional benefits/bonus package Fund
Hunter Bond
Montreal, QC
Full-time
My client - one of the world's leading quantitative trading firms - is hiring a Platform Engineer / Site Reliability Engineer (SRE) to design, build, and maintain highly scalable, resilient…
Added 56 mins ago
Site Reliability Engineer – Azure & Databricks
BULL-IT SOLUTIONS LTD
Toronto, ON
Full-time
Job Description As an Intermediate Site Reliability Engineer, you will support and continuously improve enterprise Azure and Databricks platforms. The role focuses on production…
Added 58 mins ago
Senior Staff Data Platform Engineer
Benevity
Remote, Canada
$137,800 to $178,080 CAD / year
Full-time · Remote
Benevity is seeking a talented Senior Staff Data Platform Engineer, who has an extensive record of hands-on data engineering and data product development experience. This role, reporting to…
Added 58 mins ago
Senior Staff Data Platform Engineer
Benevity
Remote, Canada
Full-time · Remote
Benevity is seeking a talented Senior Staff Data Platform Engineer, who has an extensive record of hands-on data engineering and data product development experience. This role, reporting to…
Added 1 hour ago
Senior Software Engineer
JohnIsah
Canada
Full-time
As a Senior Software Engineer on the Ecosystem Services Team, you’ll build and own back-end systems and the integrations that keep our services running, help maintain and evolve the cloud…
Added 1 hour ago
[New Grad] Applied AI Engineer
Ranger AI
Canada
Full-time
Ranger AI transforms how teams in energy, manufacturing, contracting, and pharma manage commercial operations through an AI-powered proposal management platform.
Added 1 hour ago
Senior Manager, Engineer & Build
RBC
Toronto, ON
Full-time
Partner with Platform/SRE on SLIs/SLOs, incident response, and postmortems.
Added 1 hour ago
Senior Software Developer
RBC
Toronto, ON
Full-time
We are looking for a top notch software engineer who is a great team player and obsessive about the quality of their code and delivered service. This role requires someone who can roll up…
Added 1 hour ago
RPA UiPath Platform Engineer - AI Agentic
BULL-IT SOLUTIONS LTD
Toronto, ON
Full-time
The Senior Platform Engineer develops, maintains, and manages Automation platform on premise, AWS cloud and vendor SaaS to enable automation across the bank and core operations enabling the…
Added 1 hour ago
Software Engineer III
TD
Toronto, ON
Full-time
…administration, installation, configuration / provisioning, platform planning and design, integration and release / deployment…
Added 1 hour ago
Staff Software Engineer - Full-Stack, Solution Architecture
Blazesoft
Concord, ON
Full-time
We are building an AI-centric engineering platform where brands operate as self-reliant, B2B-style customers. You will own product features end-to-end across the full stack - leveraging AI…
Added 2 hours ago
Staff Software Engineer
Okta
Toronto, ON
$160,000 to $220,000 CAD / year
Full-time
As a Staff Engineer, you’ll lead initiatives that span front-end and back-end services - delivering performant, secure, and scalable features. You’ll help define architecture, drive…
Added 2 hours ago
Lead DevOps Engineer
RBC
Toronto, ON
Full-time
…streamlining the software delivery lifecycle? As a Lead DevOps Engineer, you will play a critical role in bridging the gap between development and operations, ensuring that our applications…
Added 2 hours ago
Mechanical Design Engineer
Daedal Systems
Toronto, ON
$90,000 to $130,000 CAD / year
Full-time
Daedal Systems is looking for a Mechanical Design Engineer to support current and future development of our industrialized plasma diagnostic platform. Reporting to the technical leadership,…

Waabi

Senior / Staff ML Ops Engineer

Toronto, ON, Canada

Pay: $184,000 to $272,000 USD / year
Job type: Full-time
Posting language: English
Posted: Sep 23, 2026

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Original job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will..

Build and evolve our training infrastructure on Kubernetes with Infrastructure - GPU scheduling, autoscaling, multi-node distributed jobs, capacity strategy, and the operators and workflow engines that keep long-running training reliable.
Shape the developer-facing surface - CLIs, SDKs, job submission, templates, paved paths - designed with the teams who'll use them. Make the common case one command and keep the uncommon case possible.
Shorten the inner loop. Time to first training run, edit-to-signal latency, local iteration before a job hits the cluster, fast failure over slow mystery. Measure it, publish it, drive it down.
Evangelize best-in-class tooling and frameworks. Track what the ecosystem is shipping, evaluate honestly, and make the case with working prototypes and migration paths - or say plainly when a shiny thing isn't worth the switching cost.
Strengthen the data and artifact layer. Dataset versioning, sharding, and high-throughput loading of large multimodal sensor data, so jobs saturate GPUs instead of waiting on I/O.
Turn one-off Python into durable tooling - tested, documented, observable libraries, CLIs, and services with sane defaults, and deletions where they're overdue.
Make experiments legible, with the teams who live in them: experiment hygiene, dashboards researchers trust, a real model registry, and lineage from dataset to checkpoint to simulation result.
Ship CI/CD for models alongside autonomy and simulation, so a model change is validated the same way a code change is.
Build observability across the ML stack - utilization, throughput, failure modes, queue times, cost per experiment. When a job fails at 3am on node 47, the researcher should find out why without you.
Treat docs, onboarding, and support as product surface - golden-path guides, a new researcher productive on day two, office hours that turn repeat questions into shipped fixes.
Drive adoption, not just availability. Prototype with real users, watch them work, iterate. A tool nobody adopts didn't ship.
Make the platform boringly reliable - fewer failures, faster recovery, and none of the manual steps that quietly cost a team days.
Build guardrails that don't feel like walls, with Security, IT, and Infrastructure: access controls, data handling, and cost governance that hold up in an IP-sensitive environment while staying self-serve.

Qualifications:

5+ years of software or infrastructure engineering, including tools or platforms used by other engineers and operating ML or data-intensive production systems.
Hands-on Kubernetes expertise - GPU scheduling, autoscaling, Helm or equivalent, networking fundamentals, and the ability to debug a cluster under load rather than restart it.
Excellent Python, and a track record of designing APIs and CLIs other people enjoy using.
Practical AWS depth: object storage at scale, IAM, GPU compute, networking, cost management, and infrastructure as code (Terraform, Pulumi, or similar).
Distributed training in PyTorch (DDP, FSDP, or similar), plus experiment tracking and model registry tooling - from the perspective of someone who made them pleasant for others to use.
Fluency with containers, CI/CD, and modern build systems, including large monorepos.
The ability to influence without authority: evaluate a framework on its merits, pilot it credibly, and persuade skeptical senior engineers to change how they work.
A collaborative default - you'd rather co-own a system than draw a boundary around your part of it.
User empathy: you'd rather fix the third-most-interesting problem blocking ten people than the most interesting one blocking nobody.
Strong product instincts, strong writing, and comfort operating autonomously in ambiguous territory.
Passionate about self-driving technologies and frontier AI, and about what a small, world-class team can do with the right infrastructure.

Bonus/nice to have:

Internal developer platform, research platform, or DevEx work - with a story about a tool whose adoption you grew from zero.
Large-scale distributed GPU training: hundreds to thousands of accelerators, NCCL, high-performance cluster networking, collective communication tuning.
High-throughput loading of LiDAR or camera data, and formats such as Parquet or WebDataset.
Workflow and scheduling systems - Argo Workflows, Ray, Flyte, Kubeflow, or Slurm.
Build-system depth (Bazel or similar), including remote caching in a monorepo.
Simulation infrastructure or large-scale batch evaluation pipelines.
Background in ML, robotics, or autonomous systems infrastructure.
Security- and IP-sensitive production environments.
Open-source contributions to ML infrastructure or developer tools.

\n\n

The US yearly salary range for this role is: $184,000 - $272,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:

Competitive compensation and equity awards.
Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
Unlimited Vacation.
Flexible hours and Work from Home support.
Daily drinks, snacks and catered meals (when in office).
Regularly scheduled team building activities and social events both on-site, off-site & virtually.
As we grow, this list continues to evolve!

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

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More about this job

Responsibilities

Build and operate reliable Kubernetes-based ML training infrastructure, including GPU scheduling, distributed jobs, data and artifact systems, CI/CD, and observability. Develop and improve researcher-facing tools and workflows, drive adoption through user collaboration, and ensure the platform is secure, cost-effective, and easy to use.

Requirements

Requires 5+ years of software or infrastructure engineering experience, hands-on Kubernetes expertise, strong Python skills, and practical AWS experience. Candidates should have experience with distributed PyTorch training, developer-facing APIs and tools, containers, CI/CD, and the ability to influence teams and work collaboratively in ambiguous environments.

Skills

Kubernetes
GPU Scheduling
Python
AWS
Distributed Training
PyTorch
Terraform
Infrastructure as Code
CI/CD
Helm
Experiment Tracking
Model Registry
Developer Platforms
Distributed Systems
Data Engineering
Observability

Benefits

Competitive Compensation
Equity Awards
Medical Insurance
Dental Insurance
Vision Insurance
Unlimited Vacation
Flexible Hours
Work From Home Support
Drinks, Snacks, and Catered Meals
Team-Building Activities and Social Events

Visa sponsorship

Not detected in the job text

Keywords

Kubernetes
GPU Scheduling
Autoscaling
Distributed Training
PyTorch
DDP
FSDP
AWS
Object Storage
IAM
Terraform
Pulumi
Python
Helm
CI/CD
Containers
Experiment Tracking
Model Registry
Dataset Versioning
Multimodal Sensor Data
Argo Workflows
Ray
Flyte
Kubeflow
Slurm
Bazel
NCCL
LiDAR
Parquet
WebDataset

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