Argo AI in Pittsburgh is seeking a Software Engineer for Perception Infrastructure in our Job of the Week.
With offices in Pittsburgh, the Bay Area of California, Southeastern Michigan and Central New Jersey, we are building a high-performance team that is excited by complex engineering challenges and is passionate about making transportation safer, more affordable and accessible for all.
What you’ll do:
- Help the perception team translate their ideas to reality on the vehicle (architecture, sizing, etc.)
- Help implement algorithms on heterogeneous compute (GPU, FGPAs, TPUs, etc.) with the infrastructure teams & perception teams
- Develop APIs for the perception teams to implement their algorithm on
- Improve the latency of the system to improve its safety
What Argo AI is looking for:
- Degree in Computer Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, Physics, Robotics or a related field
- Strong software engineering skills, preferably in C++
- Strong or have a good intuition about in software design, systems and architecture
- Bonus points for Deep neural nets knowledge
- Bonus points for familiarity with GPU, CUDA, OpenCL, SIMD, heterogeneous computing, compilers, embedded and/or coming from industries like high frequency trading, game engines, real time systems
Argo AI was founded to tackle one of the most challenging applications in computer science, robotics and artificial intelligence with self-driving vehicles. Argo AI is developing and deploying the latest advancements in artificial intelligence, machine learning and computer vision to help build safe and efficient self-driving vehicles that enable these transformations and more. The challenges are significant, but we are a team that believes in tackling hard, meaningful problems to improve the world.
The perception infrastructure team owns the entire onboard perception code…except the perception algorithms! Our main area of interest is the architecture of the perception pipeline and the underlying APIs. Some example of our challenges: Are the pipelines robust and easy to use for the perception teams? Can we meet real time on the perception stack? What type of compute hardware we need? How can we make a specific subsystem or perception algorithm faster?
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