About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the team
Torc's virtual driver software utilizes cutting-edge deep learning techniques to perceive the vehicle's environment, predict the movements of other vehicles, and execute accurate driving decisions. We are actively seeking a highly experienced senior engineer to join the hardware acceleration team. This is an exceptional opportunity for you to have a significant impact on the future of the autonomous vehicle industry by enhancing AI performance.
What you'll do:
- Optimize machine learning inference models for NVIDIA Orin execution
- Leverage data parallelism and CUDA programming
- Implement tensorrt plugins
- Stay abreast of the latest advancements in PyTorch, maximizing their potential for target hardware execution
- Collaborate with machine learning engineers to develop innovative and performant deep learning solutions
- Analyze and optimize deep learning inference using profiling and optimization tools, identifying and eliminating performance bottlenecks
- Contribute to the development of internal tools and libraries to further enhance deep learning performance on the target hardware
- Document your work clearly and concisely, sharing knowledge effectively with team members
What you’ll need to Succeed:
- Bachelor's degree in computer science, data science, artificial intelligence or related field with 6+ years of professional experience or a master's degree with 3+ years of experience
- Mastery of Modern C++ (14 or more recent) and Python, with the ability to write efficient and maintainable code for both performance and flexibility
- Familiarity with object-oriented software design patterns, and their implementation in C++
- In-depth knowledge of CUDA programming and experience with optimizing deep learning kernels
- Excellent understanding of parallel computing (GPGPU) and high-performance (HPC) concepts
- Excel at working in a highly collaborative environment:
- Familiarity with AGILE development practices
- Comfortable using collaborative development tools such as Git and Jira
- Ability to adhere to company coding standards
- Proven dedication to writing production-quality code that is robust, efficient, portable, maintainable, and bug-free
Bonus points!
- Phd with 1+ years of experience
- Experience working on safety critical systems
- Experience with other relevant NVIDIA libraries and frameworks, such as CUBLAS, CuDNN, and NPP
- Deep Learning frameworks such as TensorFlow, PyTorch, or Caffe
Perks of Being a Full-time Torc’r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
- A competitive compensation package that includes a bonus component and stock options
- 100% paid medical, dental, and vision premiums for full-time employees
- 401K plan with a 6% employer match
- Flexibility in schedule and generous paid vacation (available immediately after start date)
- Company-wide holiday office closures
- AD+D and Life Insurance
At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
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