Machine Learning Systems Engineer

Toronto, ON / Remote, USA / San Francisco, CA
Engineering /
Full-Time /
About Us
We believe AI will fundamentally transform how people live and work. CentML's mission is to massively reduce the cost of developing and deploying ML models so we can enable anyone to harness the power of AI and everyone to benefit from its potential.

Our founding team is made up of experts in AI, compilers, and ML hardware and has led efforts at companies like Amazon, Google, Microsoft Research, Nvidia, Intel, Qualcomm, and IBM. Our co-founder and CEO, Gennady Pekhimenko, is a world-renowned expert in ML systems who holds multiple academic and industry research awards from Google, Amazon, Facebook, and VMware.

Do you want to help drive the development of high-performance, power-efficient datacenter solutions for Deep Learning? Do you have an interest in how system architecture across GPU, networking, CPU and IO relate to brand new generative AI capabilities? Come join our team, and bring your experience and interests to help us optimize our next generation of inference and training frameworks/frameworks and to redefine the deep learning industry once again.

As a Machine Learning Systems Engineer, you will

- Communicate with our product teams and profile ML/DL workloads to acquire an in-depth understanding of the problems.
- Design and implement novel solutions to solve the problems.
- Survey and possibly reproduce the state-of-the-art research work; analyze and evaluate if the ideas from the research work could be applied to our solutions.
- Write unit tests and benchmarks to validate and evaluate our solutions.

You may be a good fit, if you have:

    • 2+ years of experience in researching or contributing to ML/DL systems and frameworks (including the time of being a graduate student).
    • Excellent communication skills and the ability to work in a team.
    • Strong coding skills (in at least one of Python and C++).
    • Solid fundamentals in machine learning and deep learning topics.
    • Solid fundamentals in other computer science and computer engineering topics: algorithms and data structures, operating systems, computer architecture, etc.
    • Experience with GPU architecture and programming: CUDA and its related libraries and toolkits (e.g., cuDNN, cuBLAS, CUTLASS, nvprof, Nsight Compute, Nsight Systems, etc.); ROCm and its related libraries and toolkits.
    • Experience with TPU.
    • Strong academic records for candidates with bachelor’s degrees. Strong publication records in top ML/DL or computer system and architecture venues for candidates with master or PhD degrees.
Benefits & Perks
- An open and inclusive culture and work environment
- Fully stocked kitchen at the office
- Full health and dental benefits
- Parental Leave top-up for 6 months
- Continuous education budget
- Generous vacation - we're not saying unlimited, but if you need extra time to recharge, just ask

At CentML, we celebrate our differences and value cultivating an inclusive environment for all. We welcome applications of all kinds and are committed to providing an equal opportunity process.