Senior / Staff ML Onboard Optimization Engineer

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• 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

Not verified not verified - source not recorded; timestamp not recorded

Was this benefit information wrong? Tell us.

Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

74% above the BLS national median for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Schedule

Shift type

Not verified

Weekend work

Not verified

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 ML Onboard Optimization 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... - Collaborate closely with autonomy and algorithm engineers to scale safe self-driving systems using an AI-first approach. - Expand the model deployment pipeline to new GPUs and embedded systems for the next generation of our onboard compute system. - Use frameworks such as TensorRT and modelopt to optimize the models running on the truck. - Create and benchmark new CUDA kernels for inference. - Comprehensively profile model runtime and memory to pinpoint performance bottlenecks. Qualifications: - MS/PhD or Bachelors degree with a minimum of 6 years of industry experience in Computer Science, Robotics and/or similar technical field(s) of study. - Solid coding proficiency in a variety of coding languages including Python, C++ or Rust. - Experience in deep learning frameworks such as PyTorch. - Skilled in profiling CPU and GPU code using tools such as PyTorch Profiler and NVIDIA Nsight. - Experience with Nvidia embedded platforms such as Nvidia Jetson or

Read the full description at jobs.lever.co. FewerJobs shows a source-linked preview and links to the original posting.