Senior / Staff Software Engineer, ML Datasets & Data Pipelines
Toronto, ON
- Pay
USD 148,000–260,000/yearLocation-specific pay — pay source
Experience working with multimodal sensor data (e.g., LiDAR, RADAR, camera). The US yearly salary range for this role is: $148,000 - $260,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus. Perks/Benefits:
Read the full posting- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign and implement data pipelines using real-world driving data and simulation
Optimize data formats, caching, and dataloading for efficient ML training at scale
Improve data sampling and composition to track model performance and find edge cases
Write high-quality, well-tested code
Help plan the project roadmap, priorities, and delivery
From the employer’s posting
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.
What you’ll bring
All qualificationsCore experience
- Proficiency in Python and strong software engineering fundamentals, including experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Experience with optimizing large scale distributed training pipelines and/or highly optimized ML inference pipelines.
- Hands-on experience building distributed ETL and data processing pipelines.
- Experience with MapReduce (Apache Hadoop/Spark) or orchestration frameworks (Apache Airflow, Apache Beam, Google Cloud Dataflow, AWS Step Functions).
- Strong understanding of cloud job orchestration, monitoring, and instrumentation best practices.
- Experience solving data challenges specific to autonomous driving.
Qualification wording
Proficiency in Python and strong software engineering fundamentals, including experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Experience with optimizing large scale distributed training pipelines and/or highly optimized ML inference pipelines.
Hands-on experience building distributed ETL and data processing pipelines.
Experience with MapReduce (Apache Hadoop/Spark) or orchestration frameworks (Apache Airflow, Apache Beam, Google Cloud Dataflow, AWS Step Functions).
Strong understanding of cloud job orchestration, monitoring, and instrumentation best practices.
Experience solving data challenges specific to autonomous driving.
Tools in this posting
- Python
- AWS
- Hadoop
- Spark
- Airflow
- PyTorch
- TensorFlow
- GCP
Source — Tool mentions in context
- 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.
- 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.
Posting record
Report an errorOpen 6 monthsWe first saw this posting 198 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 14, 2026 · 198 days ago
- Recorded sightings
- 157
- Last seen by us
- Oct 30, 2026
- Employer says posted
- Mar 26, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on jobs.lever.co. The employer’s form will show what is required.
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Job description
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).
The US yearly salary range for this role is: $148,000 - $260,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve!
Employment type
Full-time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Experience working with multimodal sensor data (e.g., LiDAR, RADAR, camera). The US yearly salary range for this role is: $148,000 - $260,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus. Perks/Benefits:
- Location & working pattern
Toronto, ON
- Daily drinks, snacks and catered meals (when in office). - Regularly scheduled team building activities and social events both on-site, off-site & virtually. - As we grow, this list continues to evolve!
- Work authorization
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! 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. Employment type
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