Machine Learning Infrastructure Engineer
San Francisco, CA

Job Description

AI Foundation is currently looking to add a software engineer to work closely with researchers to bring to production ideas across multiple disciplines: speech, natural language processing, and computer vision.

What this candidate will bring to the table:

* Understanding of system level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO
* Professional experience writing performant scientific, numerical and parallel code in a data-driven research environment
* Experience in performance profiling and characterization
* Understand how to optimize things like cache locality and CPU core count vs clock speed
* Experience building and maintaining software libraries
* Good communication and organization skills, with a logical approach to problem-solving, good time management, and task prioritization skills

Specific skill sets this candidate will have:

* Experience with deep learning frameworks: PyTorch (preferable), Tensorflow
* Experience using Cython, Numba, C or similar to speed up analytical code
* Experience writing and optimizing code in a vectorized scripting language (numpy or similar BLAS/LAPACK wrapper)
* Strong knowledge of C/C++, Python, software design, programming techniques, and AI algorithms
* Experience with GPU acceleration (CUDA and CUDNN)
* Maintaining large scientific python codebases
* Dealing with issues of providence and experimental repeatability
* High-Performance Computing (HPC)

What we can offer:

This is a mid- or senior-level engineering role and we offer a competitive salary, valuable stock options and comprehensive benefits that allow individual flexibility for all employees to choose what makes the most sense for their personal situation.

AI Foundation is committed to a culture of flexibility, diversity, and fun for all of our employees. We are working on some of the most challenging technical problems and we know the solutions will come from all of us working together in an inclusive, transparent and open manner.