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Added 2 months ago
ML Engineer
Tigera
Vancouver, BC
…potentially publish your research, speak at conferences (KubeCon, AI Engineer Summit, security research venues), and represent Tigera in the technical community. This is a real opportunity…
Added 2 months ago
A
Senior Site Reliability Developer
Autodesk
Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
- Full-time
Relevant certifications (e.g., AWS Certified DevOps Engineer, AWS Site Reliability Engineer)
Added 2 months ago
P
Senior Robotics Engineer - Capture Systems
Peripheral
Toronto, ON
- Full-time
…Our models generate spatial data, used for advanced sports analytics and immersive media experiences. We’re solving key research challenges in 3D computer vision, creating the foundations…
Added 2 months ago
P
Senior Machine Learning Engineer - Reconstruction
Peripheral
Toronto, ON
- Full-time
…Our models generate spatial data, used for advanced sports analytics and immersive media experiences. We’re solving key research challenges in 3D computer vision, creating the foundations…
Added 2 months ago
P
Infrastructure Engineer - Platform
Peripheral
Toronto, ON
- Full-time
…Our models generate spatial data, used for advanced sports analytics and immersive media experiences. We’re solving key research challenges in 3D computer vision, creating the foundations…
Added 2 months ago
RB
Staff Engineer – Software Development, Architecture, Security & Governance
Royal Bank of Canada
Toronto, ON
- Full-time
We are seeking a highly skilled and experienced Staff Engineer to join our Enterprise Architecture team, leveraging their expertise in full-stack development, backend engineering, API…
Added 1 month ago
Senior GCP Data Engineer
Capgemini
Mississauga, ON
GCP Certifications (e.g., Professional Data Engineer). Experience with real-time processing, Vertex AI, or multi-cloud environments. Key Responsibilities Pipeline Development: Build and…
Added 1 month ago
GS
Senior Software Engineer
Guidewire Software
Mississauga, ON · Toronto, ON
- Full-time
As a Senior Full‑Stack Software Engineer, you will design and build elegant, high‑impact capabilities for insurance content transformation and modeling, advancing Guidewire’s shift toward…
Added 2 months ago
Ingénieur Data / Data Engineer
mthree Recruiting Portal
Montreal, QC
We are looking for someone to be a part of a dynamic team as a Data Engineer for one of our clients. This position is for a data engineering role in the MongoDB and Kafka squad. We are a…
Added 2 months ago
M
Systems Engineer – Satellite Ground Segment
MDA
Richmond, BC
- Full-time
We’re looking for a Systems Engineer – Satellite Ground Segment in our Geointelligence Engineering Team at our Richmond office.
Added 2 months ago
C
Full Stack Software Engineer
Citi
Mississauga, ON
- Full-time
We are hiring a Full Stack Engineer to design, build and maintain a critical Cash & Intraday Liquidity Management platform. This platform sits at the intersection of engineering ambition…
Added 3 months ago
E
Senior Backend Engineer, Entities
EvenUp
Toronto, ON
- $184,728 to $249,926 USD / year
- Full-time
Growth & Collaboration: Grow as an engineer working alongside world-class peers on impactful, cutting-edge generative AI projects.
Added 3 months ago
T
Founding Technical Recruiter
Terminal
Toronto, ON
- $115,000 to $152,000 USD / year
- Full-time
Added 3 months ago
P
Inference Optimization Engineer
PolarGrid
Remote, Canada
- Full-time
- Remote
PolarGrid is building the infrastructure layer for real-time AI inference. We're looking for an Inference Optimization Engineer to squeeze every bit of performance out of our stack. You'll…
Added 3 months ago
Q-
DevOps - MLOps engineer
QUANTEAM - North America (RAINBOW PARTNERS Group)
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
We are looking for a DevOps - MLOps engineer for one of our clients.
Added 3 months ago
EA
Site Reliability Engineer III
Electronic Arts (EA)
Toronto, ON
- Full-time
As a Site Reliability Engineer, your role covers the entire lifecycle of a product-- from helping developers with architecture and delivery to on-call incident response and triage. Your…
Added 3 months ago
ES
Machine Learning Engineer - EA Sports FC
EA SPORTS
Vancouver, BC
- Full-time
Reporting to the Senior Data Science Manager, we are seeking a full-stack Machine Learning Engineer to operationalize, deploy, and scale high-impact machine learning solutions and…
Added 3 months ago
EA
Site Reliability Engineer III
Electronic Arts (EA)
Vancouver, BC
- Full-time
As a Site Reliability Engineer, your role covers the entire lifecycle of a product-- from helping developers with architecture and delivery to on-call incident response and triage. Your…
Added 3 months ago
EA
Site Reliability Engineer III
Electronic Arts (EA)
Victoria, BC
- Full-time
As a Site Reliability Engineer, your role covers the entire lifecycle of a product-- from helping developers with architecture and delivery to on-call incident response and triage. Your…
Added 3 months ago
C
Lead Azure Data Engineer (contract)
Capgemini
Brampton, ON
- Contract
Create and maintain data tools that enable analytics and data science teams to build, optimize, and scale business solutions.
Added 3 months ago
J
Forward Deployed Engineer, Supply Chain
Jetson
North Vancouver, BC
- Full-time
We're building a new kind of role to help us scale: the Forward Deployed Engineer (FDE). The title was originally coined for engineers embedded with external customers, and we've pointed…
Added 3 months ago
T(
Principal Data Engineer
Tilt (f.k.a. Delphia)
Remote, Canada
- $210,000 to $270,000 USD / year
- Full-time
- Remote
We're looking for a Principal Data Engineer who thrives in ambiguity, enjoys building large-scale data platforms, and wants to define how AI-native investing is powered behind the scenes.
Added 2 months ago
TT
AI/ML Engineer
TC Transcontinental
Mississauga, ON
- Full-time
We are looking for an AI/ML Engineer to work on building a multi-tenant, AI-driven promotional content platform for our customers.
Added 1 month ago
Lead Developer, Tools
2K
Montreal, QC
A Lead Developer focused on pipeline products and data systems. You are a multi-functional engineer who loves building software across all tech stacks. You might develop a data warehouse…
Added 1 month ago
R
Senior Machine Learning Engineer
Remitly
Burnaby, BC
- Full-time
As a Senior Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our AI strategy. The Core AI/ML team is responsible for building the foundational machine…

Peripheral

Infrastructure Engineer - Platform

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Experience: 4+ years of experience building and operating production cloud infrastructure, ideally for ML workloads.
Posting language: English
Posted: Aug 10, 2026

Original job description

WHO WE ARE:

Peripheral is developing spatial intelligence, starting in live sports and entertainment. Our models generate spatial data, used for advanced sports analytics and immersive media experiences. We’re solving key research challenges in 3D computer vision, creating the foundations for the next generation of robotic perception and embodied intelligence.

We’re backed by top investors, including Khosla Ventures, Inovia, Deloitte Ventures, Daybreak, and Entrepreneurs First, and working with some of the biggest names in sports. Our team includes engineers and researchers from leading technology companies and research institutions, and we’re building technology at the intersection of AI, graphics, and the future of live entertainment. We’re ambitious and looking to win.

THE OPPORTUNITY:

We’re seeking an experienced Infrastructure Engineer to architect and build the cloud infrastructure that powers Peripheral, from large-scale foundation model training to reliable inference during live events.

You’ll work directly with our CTO and in collaboration with research and engineering teams to turn models and modules into scalable production systems. This is a highly architectural role that requires strong systems thinking and deep experience in DevOps and MLOps. You should understand how backend systems fail and evolve as usage grows and anticipate and design the architecture, processes and tooling to scale reliably.

You’ll help define how systems across Peripheral work together to deliver spatial experiences to customers. At the same time, you’ll build the infrastructure that keeps our research velocity high, including setting up and maintaining ML training clusters, distributed training infrastructure with PyTorch, and optimized multi-view video data loading.

The role is highly cross-functional and hands-on. You’ll build working knowledge across capture systems, robotics, foundation model training, and production inference to support teams across Peripheral while keeping customer-facing systems reliable. We’re also looking for someone who can mentor others as the team grows, maintain clear documentation in a fast-moving environment, and ship high-quality infrastructure with strong attention to detail.

WHO YOU ARE:

You’ve built and scaled production cloud infrastructure and are comfortable owning systems end to end, from large-scale training workloads to reliable model serving.

You think in terms of systems, tradeoffs, and failure modes. Cost, latency, reliability, security, and developer productivity are all first-class concerns, and you know how to balance long-term architecture with pragmatic execution.

You collaborate well across research and engineering, communicate clearly, value strong documentation, and can provide technical leadership and mentorship as the infrastructure function grows.

You’re excited to help shape Peripheral’s infrastructure culture from the ground up, establishing the tooling, standards, and practices the broader engineering organization will build on as the company scales.

WHAT YOU’LL BE DOING:

Design, build, and operate cloud infrastructure for large-scale ML training, including GPU/TPU compute, job orchestration, and experiment tracking.
Partner with research to scale foundation model training workflows, including distributed PyTorch training and efficient multi-view video data loading.
Build and operate production infrastructure for model deployment and serving, with a focus on reliability, latency, scalability, and cost.
Design reliable data pipelines for moving multi-view video, LiDAR, and other sensor data from capture through customer-facing outputs.
Work across research and engineering to translate infrastructure needs into scalable, self-serve systems and developer tooling.
Establish standards for infrastructure-as-code, CI/CD, monitoring, observability, security, and cloud operations.
Improve the reliability and resilience of customer-facing systems during live, time-sensitive workloads.
Mentor engineers and interns as the infrastructure function grows.

REQUIREMENTS

Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
4+ years of experience building and operating production cloud infrastructure, ideally for ML workloads.
Deep expertise in AWS or GCP, with the ability to work effectively across both.
Experience building distributed training infrastructure, including GPU/TPU clusters, job scheduling, orchestration, and large-scale training workloads.
Experience deploying and operating production ML inference systems with strong requirements around reliability, latency, scalability, and cost.
Track record of operating production systems at meaningful user scale and maintaining reliability under growing load.
Strong experience with infrastructure-as-code, containers, and orchestration tools such as Terraform, Kubernetes, and Docker.
Strong understanding of cloud security, networking, observability, and operational best practices.
Comfortable working cross-functionally across research, product, and hardware teams that generate and consume data.
Must have the legal right to work in Canada and be willing to relocate to Toronto for an in-office role. We are unable to provide immigration sponsorship at this time.

NICE TO HAVE

Experience with AWS and GCP services such as S3, EC2, ECR, Batch, ParallelCluster, SageMaker, GCS, Cluster Toolkit, or equivalent infrastructure.
Experience with ML infrastructure and tooling such as Weights & Biases, MLflow, CVAT, and Hugging Face.
Experience with high-throughput ingestion or streaming systems such as Kafka, Pub/Sub, or Kinesis, particularly for video, point clouds, or other large sensor data.
Experience with real-time video, low-latency streaming, CDNs, or large-scale data delivery systems.
Experience optimizing ML systems, including data loading, distributed training, GPU utilization, or custom kernels.
Prior ML research or ML systems experience, including publications, patents or open-source contributions.
Experience as an early or founding infrastructure or platform engineer at a startup.
Experience mentoring junior engineers or intern

WHY YOU’LL LOVE WORKING HERE

Competitive equity package as an early team member.
Annual salary of $150K–$200K CAD plus performance bonuses, commensurate with experience.
Unparalleled access to premier global sporting events and iconic venues.
Full ownership of high-impact projects shaping the future of spatial intelligence and 3D media.
Flexible Paid Time Off (PTO).
Comprehensive health, dental, vision, and wellness benefits.

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More about this job

Responsibilities

You will architect and build scalable cloud infrastructure to support large-scale foundation model training and reliable production inference for live events. The role involves collaborating with research and engineering teams to design self-serve systems, developer tooling, and resilient data pipelines.

Requirements

Candidates must have at least 4 years of experience in production cloud infrastructure, specifically with ML workloads and distributed training. Proficiency in AWS or GCP, infrastructure-as-code tools like Terraform and Kubernetes, and the ability to work on-site in Toronto are required.

Skills

Cloud infrastructure
MLOps
DevOps
AWS
GCP
Distributed training
PyTorch
Kubernetes
Terraform
Docker
Infrastructure-as-code
CI/CD
Observability
System architecture
GPU compute
Data pipelines

Benefits

Competitive equity package
Performance bonuses
Access to global sporting events
Flexible paid time off
Health benefits
Dental benefits
Vision benefits
Wellness benefits

Visa sponsorship

Not detected in the job text

Keywords

Infrastructure Engineer
Cloud Infrastructure
MLOps
DevOps
AWS
GCP
PyTorch
Kubernetes
Terraform
Docker
GPU
TPU
Distributed Training
CI/CD
Observability
Spatial Intelligence
Computer Vision
Data Pipelines
Latency
Scalability
Reliability
Infrastructure-as-code
Networking
Cloud Security
Foundation Models
Inference
Multi-view Video
Robotics
System Architecture
Platform Engineering

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