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About the Role

Waabi is a leader in Physical AI, developing technology for autonomous transportation. We are seeking innovative and collaborative candidates to join our world-class team and impact the future of autonomous driving.

Responsibilities

Build and evolve training infrastructure on Kubernetes, including GPU scheduling, autoscaling, and distributed job management.
Shape the developer-facing surface with CLIs, SDKs, and job submission tools.
Shorten the inner loop for training jobs, focusing on iteration speed and fast failure.
Evangelize best-in-class tooling and frameworks, evaluating ecosystem offerings.
Strengthen the data and artifact layer for efficient loading of large multimodal sensor data.
Transform one-off Python scripts into durable, tested, and documented tooling.
Make experiments legible through experiment hygiene, dashboards, model registry, and lineage tracking.
Ship CI/CD for models, ensuring validation comparable to code changes.
Build observability across the ML stack, covering utilization, throughput, and costs.
Treat docs, onboarding, and support as product surface, providing guides and support.
Drive adoption of tools through prototyping and user feedback.
Ensure platform reliability with fewer failures and faster recovery.
Build guardrails for security, IT, and infrastructure, including access controls and cost governance.
Develop internal developer platforms and DevEx tools.
Manage large-scale distributed GPU training with hundreds to thousands of accelerators.
Optimize high-throughput loading of LiDAR or camera data.
Implement workflow and scheduling systems.
Deepen build-system expertise, including remote caching in monorepos.
Develop simulation infrastructure or large-scale batch evaluation pipelines.
Work with security- and IP-sensitive production environments.
Contribute to open-source ML infrastructure or developer tools.

Requirements

5+ years of software or infrastructure engineering experience, including tools/platforms for engineers and operating ML/data-intensive production systems.
Hands-on Kubernetes expertise, including GPU scheduling, autoscaling, Helm, networking, and cluster debugging.
Excellent Python skills with a track record of designing user-friendly APIs and CLIs.
Practical AWS depth, including object storage, IAM, GPU compute, networking, cost management, and infrastructure as code.
Experience with distributed training in PyTorch and experiment tracking/model registry tooling.
Fluency with containers, CI/CD, and modern build systems, including large monorepos.
Ability to influence without authority, evaluate frameworks, and persuade engineers.
Collaborative approach to system ownership.
Strong user empathy and focus on solving user-blocking problems.
Strong product instincts, writing skills, and comfort operating autonomously in ambiguous territory.
Passion for self-driving technologies and frontier AI.
Experience with internal developer platforms, research platforms, or DevEx work.
Experience with large-scale distributed GPU training (hundreds to thousands of accelerators).
Experience with high-throughput loading of LiDAR or camera data.
Experience with workflow and scheduling systems.
Build-system depth (Bazel or similar), including remote caching.
Experience with simulation infrastructure or large-scale batch evaluation pipelines.
Background in ML, robotics, or autonomous systems infrastructure.
Experience in security- and IP-sensitive production environments.
Open-source contributions to ML infrastructure or developer tools.

Skills

Kubernetes
GPU scheduling
Autoscaling
Helm
Python
API design
CLI design
AWS
Object storage
IAM
GPU compute
Networking
Cost management
Infrastructure as Code
Terraform
Pulumi
PyTorch
DDP
FSDP
Experiment tracking
Model registry
Containers
CI/CD
Build systems
Monorepos
ML infrastructure
Developer tools
LiDAR data loading
Camera data loading
Parquet
WebDataset
Argo Workflows
Ray
Flyte
Kubeflow
Slurm
Bazel
Remote caching
Simulation infrastructure
Batch evaluation
Robotics infrastructure
Autonomous systems infrastructure
NCCL
Collective communication tuning

Location

Toronto
San Francisco
Dallas
Pittsburgh

Work Type

Full-time

Experience Level

5+ years of software or infrastructure engineering experience

Salary/Compensations

$184,000 - $272,000 USD

Benefits

Competitive compensation and equity awards
Health and Wellness benefits (Medical, Dental, Vision)
Unlimited Vacation
Flexible hours
Work from Home support
Daily drinks, snacks and catered meals (when in office)
Regularly scheduled team building activities and social events

About the Company

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!

Equal Opportunity

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.