Senior / Staff Software Engineer, ML Datasets & Data Pipelines

Waabi

Toronto

Presencial

CAD 120.000 - 190.000

Jornada completa

14 días+

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Descripción de la vacante

Waabi, a leader in Physical AI, seeks a Senior/Staff Software Engineer to build scalable ML data pipelines for training and evaluating autonomous driving tech. You will work with world-renowned scientists to solve challenging data problems and accelerate driverless vehicle launches.

You will design data pipelines, optimize performance, and manage ML datasets. Collaboration with cross-functional teams and mentorship of junior engineers are key parts of this role, based in Toronto with global

Formación

  • BS or MS in Computer Science or a related technical field with 4+ years of industry experience.
  • Proficiency in Python and 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 and dataloading.
  • Strong understanding of cloud job orchestration, monitoring, and instrumentation best practices.
  • Collaborative, open-minded approach with a passion for tackling hard autonomous technology problems and mentoring others.

Responsabilidades

  • Design and implement data pipelines using real-world driving data and Waabi World to train and evaluate deep learning models.
  • Optimize data formats, caching, and dataloading for efficient ML training and evaluation at scale.
  • Improve data sampling and composition for deep data introspection to track model performance and edge cases.
  • Champion engineering excellence by writing high-quality, well-structured, and rigorously tested code.
  • Help drive project roadmap planning, prioritization, and delivery.

Conocimientos

Python
Deep Learning
ETL Pipelines
ML Pipelines
PyTorch
TensorFlow
JAX
Cloud Orchestration
Mentoring

Educación

BS in Computer Science
MS in Computer Science

Descripción del empleo

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

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 driving data 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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