Senior / Staff ML Training Optimization Engineer

Job Description

Job Description

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:

You will...

- Build standardized distributed training frameworks for research and production, drive our training towards new levels of stability and efficiency.

- Comprehensively profile model runtime and memory to pinpoint performance bottlenecks.

- Identify and evaluate emerging technologies that can be adopted into Waabi’s training and inference frameworks. Examples include designing new CUDA kernels, quantization-aware training and inference, and compilation/deployment techniques.

- Work with researchers and ML engineers on best-practices for optimal resource usage.

- Create and improve tooling and dashboards to ensure broad adoption of your work.

Qualifications:

- MS/PhD or Bachelors degree with a minimum of 4 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 or Jax.

- Skilled in profiling CPU and GPU code using tools such as PyTorch Profiler and NVIDIA Nsight.

- Open-minded and collaborative team player with willingness to help others.

- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.

Bonus/nice to have:

- Experience in identifying when custom CUDA kernels are needed, and implementing them.

- Experience in Bazel in a monorepo environment, and integrating third party packages into dev environments.

- Experience with Kubernetes-based training platforms.

The US yearly salary range for this role is: $141,000 - $249,000 in addition to competitive perks & benefits. Waabi’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:

Waabi provides a competitive benefits package that includes:

- Competitive compensation and equity awards.

- Health and Wellness benefits encompassing Medical, Dental and Vision coverage.

- 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.

- World-class facility that includes a gym, games room (ping pong table, video game consoles, board games, etc), multiple collaborative working spaces and a gorgeous patio!(when in office)

- As we grow, this list continues to evolve! 

Waabi is an equal opportunity employer that celebrates diversity and is committed to creating a supportive, inclusive, and accessible environment for all employees. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.