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Salary
$142k – $246k per year (Estimated)
Location
Remote/Hybrid (Toronto, Canada)
Seniority
Staff · 4+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Waabi is an artificial intelligence and autonomous vehicle technology company headquartered in Toronto, Canada, founded in 2021. The company develops an end-to-end artificial intelligence software platform, known as the Waabi Driver, and a simulation environment called Waabi World to power autonomous trucks and robotaxis. It operates primarily in the North American logistics and transportation sectors through strategic partnerships with industry leaders such as Volvo, Uber Freight, and NVIDIA.

As a Senior/Staff Software Engineer embedded within our Autonomy & Algorithms team, you will build the scalable ML data pipelines necessary to train and evaluate Waabi’s autonomous driving platform. Working closely with world-renowned scientists and engineers, you will solve complex data challenges to accelerate our launch of fully driverless vehicles.

You Will..

- Design and implement data pipelines using real-world drivingdata and Waabi World (our high-fidelity simulator) to train and evaluate deep learning models.

- Optimize data formats, caching, and dataloading to drive highly efficient ML training and evaluation at scale.

- Improve data sampling and composition for deep data introspection to track model performance and uncover critical edge-case scenarios.

- Champion engineering excellence by writing high-quality, well-structured, and rigorously tested code.

- Help drive project roadmap planning, prioritization, and delivery.

Qualifications:

- BS or MS in Computer Science, Machine Learning, or a related technical field, with 4+ years of industry experience.

- Proficiency in Python and strong software engineering fundamentals, including experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.

- Hands-on experience building distributed ETL and data processing pipelines.

- Direct experience managing ML pipelines, including dataset management, dataloading, and optimization.

- Strong understanding of cloud job orchestration, monitoring, and instrumentation best practices.

- A collaborative, open-minded approach with a passion for tackling hard problems in autonomous technology and a strong willingness to mentor others.

Bonus Points:

- Experience with optimizing large scale distributed training pipelines and/or highly optimized ML inference pipelines.

- Experience with MapReduce (Apache Hadoop/Spark) or orchestration frameworks (Apache Airflow, Apache Beam, Google Cloud Dataflow, AWS Step Functions).

- Experience solving data challenges specific to autonomous driving.

- Familiarity with linear algebra (projections, transforms) and 3D geometry.

- Experience working with multimodal sensor data (e.g., LiDAR, RADAR, camera).

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