Senior Software Engineer, Auto Labelling

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$170K-$220K From the posting source checked Jun 20, 2026

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Software Engineer, Auto Labelling Remote US & Canada 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 You will... - Be part of a team of multidisciplinary Research Scientists and Engineers working on building a cutting-edge offline perception and auto-labelling system leveraging computer vision, and machine learning. - Manage the end-to-end orchestration of the large-scale auto-labelling training, evaluation and automation eco-system. - Architect and scale the pipeline to handle large-scale data and user requests using distributed computing frameworks. - Collaborate with ML researchers and engineers to seamlessly deploy new architectures into the production environment. Qualifications: - Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study. - 3+ years of experience developing solutions in ML systems or the ML software stack. - Deep understanding of ML system architecture, performance analysis, and profiling tools to optimize complex workloads. - Experience with the end-to-end productionization of deep learning models, particularly large-scale online inference. - Proficient in Python with a track record of writing high-quality, well-structured, and well-tested "production-grade" code. - Open-minded

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