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Software Engineer – Labelling, Data & Automation

waabi · Toronto

New
Mid 🇬🇧 English
Python Airflow Beam Dataflow Hadoop Spark Terraform CloudFormation ML pipelines embedding models

Job description

About the role

Waabi is building the next generation of autonomous transportation. As a Software Engineer on the Labelling and Data Automation team you will create pipelines, tools, and workflows that accelerate the development of AI‑first self‑driving technology.

Key responsibilities

  • Design and implement tools, pipelines, and metrics to accelerate the AI‑first autonomy system and generative AI simulator.
  • Own the process and tooling for efficiently finding relevant data across petabytes of real‑world data.
  • Build high‑reliability systems for extracting and labeling data with vendors and integrate them back into Waabi’s platform.
  • Collaborate with internal and third‑party stakeholders to define taxonomy, validation rules, and success criteria for labeling projects.
  • Deploy end‑to‑end data solutions delivering high‑quality labeled data for ML teams.
  • Deploy open‑set/embedding models to production, enabling new search and curation modalities.
  • Champion engineering excellence with well‑structured, tested code and contribute to roadmap planning.

Required profile

  • 4+ years of industry experience.
  • Bachelor’s degree in computer science, engineering, machine learning or a related field.
  • Proven ability to write high‑quality, well‑tested Python code.
  • Strong experience building large‑scale data pipelines and processing frameworks.
  • Understanding of cloud job orchestration, monitoring and instrumentation best practices.
  • Excellent communication and organizational skills.

Required skills

  • Python programming
  • Large‑scale data pipeline development
  • Cloud orchestration tools (e.g., Airflow, Beam, Dataflow)
  • MapReduce frameworks such as Hadoop or Spark
  • Infrastructure as code (Terraform, CloudFormation)
  • Experience with ML pipelines and embedding models

Questions fréquentes

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Source : ats:lever

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Published 18 hours ago

Expires 1 month from now

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waabi

Toronto