Machine Learning Systems Engineer
Description For Machine Learning Systems Engineer
CentML is on a mission to revolutionize AI accessibility by significantly reducing the costs associated with ML model development and deployment. Led by a distinguished team of AI, compiler, and ML hardware experts from industry giants like Amazon, Google, Microsoft Research, and Nvidia, the company is at the forefront of ML systems innovation. Their co-founder and CEO, Gennady Pekhimenko, brings world-renowned expertise in ML systems with multiple academic and industry research awards.
As a Machine Learning Systems Engineer, you'll be instrumental in developing high-performance, power-efficient datacenter solutions for Deep Learning. The role combines cutting-edge work in GPU architecture, networking, CPU, and IO systems, particularly focusing on next-generation inference and training frameworks. You'll work with advanced generative AI capabilities and help optimize systems that are reshaping the deep learning industry.
The position requires a strong background in ML/DL systems, excellent coding abilities in Python or C++, and deep understanding of computer architecture and GPU programming. You'll be joining a company that values diversity, offers competitive benefits, and provides an environment where you can make a significant impact on the future of AI technology. The hybrid work model offers flexibility while maintaining collaborative opportunities in either Toronto or San Francisco Bay Area offices.
Responsibilities For Machine Learning Systems Engineer
- Communicate with product teams and profile ML/DL workloads
- Design and implement novel solutions to solve problems
- Survey and reproduce state-of-the-art research work
- Write unit tests and benchmarks to validate and evaluate solutions
Requirements For Machine Learning Systems Engineer
- 2+ years of experience in ML/DL systems and frameworks
- Excellent communication skills and ability to work in a team
- Strong coding skills in Python and/or C++
- Solid fundamentals in machine learning and deep learning
- Knowledge of algorithms, data structures, operating systems, and computer architecture
- Experience with GPU architecture and programming (CUDA, cuDNN, cuBLAS, CUTLASS)
- Experience with TPU
- Strong academic records or publication records in ML/DL or computer systems
Benefits For Machine Learning Systems Engineer
- Open and inclusive work environment
- Employee stock options
- Best-in-class medical and dental benefits
- Parental Leave top-up
- Professional development budget
- Flexible vacation time
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