We’re Cruise, the self-driving ride-hailing service.
We are building the world’s most advanced self-driving vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.
At Cruise, our engineers have opportunities to grow and develop while learning from leaders at the cutting-edge of their fields. With a culture of internal mobility, there's opportunity to thrive in a variety of disciplines. This is a place for dreamers and doers to succeed.
If you are looking to solve one of today’s most complex engineering challenges, see the results of your work in hundreds of self-driving cars, and make a positive impact in the world starting in our cities, join us.
The Autonomous Vehicle (AV) software stack heavily relies on machine learning techniques to perform a variety of tasks, each with different requirements of hardware/compute resources. Throughout the life-cycle of each machine learning model, skilled ML engineers (on both training and inference sides) work closely to prepare it for a robust, scalable, and compute/power efficient inferencing on a resource-constrained hardware accelerator. Such a close working relationship is key to fast and successful deployment of intelligent systems on the car.
Cruise is looking for a deep learning compiler engineer to build the compiler and software tool chain for deploying machine learning models on to a variety of ML hardware accelerators. In this position, you will contribute, develop and enhance Cruise’s internal ML compiler infrastructure for high-performance and retargetability possibly by leveraging open-source technology like LLVM, TVM and XLA.
In this role, you will collaborate closely with engineers from different AV Engineering teams (e.g. Computer Vision, Perception, platform) to scope out system/software requirements at the application level while engaging with AV hardware teams to understand the target hardware platform and its constraints.
If you're interested in optimizing machine learning inference on different hardware accelerators, and want to test your skills with real-world (and practical) applications in the autonomous vehicle domain, let's chat!
- Design, implement and test compiler features and capabilities related to IR infrastructure and compiler passes
- Develop graph compiler optimizations like operator fusion, layout optimization, etc that are customized to each of the different ML accelerators in the system
- Integrate open-source and vendor compiler technology in to Cruise’s internal compiler infrastructure
- Build performance tooling to evaluate, understand and improve ML performance on different accelerators
- Collaborate with cross functional agile teams of AV engineers to guide the direction of inferencing and provide requirements and feature requests for hardware vendors
- Closely follow industry and academic developments in the ML compiler domain and provide performance guidelines and best practices for other ML engineers
What you must have:
- 5+ years of experience in the field of compiler design and 2+ years of experience with deep learning
- Experience with deep learning frameworks (e.g., Tensorflow, etc) and software stack (e.g., TensorRT, TVM, etc)
- Experience with ML accelerators and hardware architecture
- Strong expertise in writing production quality C++ code
- Comfortable and experienced in software development lifecycle - coding, debugging, optimization, testing, integration
- Familiarity with parallelization techniques for ML acceleration
- MS, or higher degree, in CS/CE/EE, or equivalent, in industry experience
- GPU programming (CUDA) and familiarity with deep learning stack (e.g., cuDNN, cuBLAS)
- SIMD programming (avx2, neon)
- Experience with open-source deep learning stacks (TVM, XLA, etc)
- Our benefits are here to support the whole you:
- Competitive salary and benefits
- 401(k) Cruise matching program
- Medical / dental / vision, AD+D and Life
- Flexible vacation and company paid holidays
- Healthy meals and snacks provided
- Paid parental leave & family expansion stipend
- Monthly wellness stipend
- Commuter benefits
- We’re Integrated
- Through our partnerships with General Motors and Honda, we are the only self-driving company with fully integrated manufacturing at scale.
- We’re Funded
- GM, Honda, SoftBank, and T. Rowe Price have invested billions in Cruise. Their backing for our technology demonstrates their confidence in our progress, team, and vision and makes us one of the leading autonomous vehicle organizations in the industry. Our deep resources greatly accelerate our operating speed.
- We’re Independent
- We have our own governance, board of directors, equity, and investors. Our independence allows us to not just work on the bleeding-edge of technology, but also define it.
- We’re Vested
- You won’t just own your work here, you’ll have the potential to own equity in Cruise, too. We are competing in a market that is projected to grow exponentially, which gives our company valuation room to grow.
Cruise LLC is an equal opportunity employer. All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis. Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with Cruise to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions is entirely voluntary. Any information you choose to provide will be kept confidential, and will not impact the hiring decision in any way.
We also consider for employment qualified applicants regardless of criminal histories, consistent with applicable laws. And, if you believe that you will need any type of accommodation, please let us know.
Note to Recruitment Agencies: Cruise does not accept unsolicited agency resumes. Furthermore, Cruise does not pay placement fees for candidates submitted by any agency other than its approved partners.