Senior Staff ML Training Optimization Engineer
Share
Job Location:
Dallas, IA - USA
Monthly Salary:
$ 141000 - 249000
Posted on:
8 hours ago
Vacancies:
1 Vacancy
Job Summary
Waabi founded by AI visionary Raquel Urtasun is the leader in Physical AI. With a world-class team were unlocking the next era of autonomous transportation with technology thats 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 Waabis 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: $141000 - $249000 in addition to competitive perks & benefits. Waabis yearly salary ranges are determined based on several factors in accordance with the Companys 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. 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.
Required Experience:
Staff IC
