Senior / Staff Machine Learning Infrastracture Engineer
Waabi - Remote US & Canada
Posted Apr 13, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- $157K-$234K From the posting source checked Jun 20, 2026
Was this benefit information wrong? Tell us.
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
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Senior / Staff Machine Learning Infrastracture Engineer 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.. - Design, develop, and implement the machine learning platform for the continuous deployment and integration of machine learning models. - Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes. - Automate the training, testing and deployment processes for machine learning models. - Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability. - Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness. - Ensure compliance with security and data privacy standards in all MLOps activities. Qualifications: - 3-5 years of experience supporting machine learning training platforms. - Bachelor's degree in Computer Science, Data Science or a related field. - Strong understanding of machine learning principles and model lifecycle management. - Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch. - Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning
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