Machine Learning Systems Engineer

Sorry, this job was removed at 06:05 p.m. (CST) on Friday, Apr 18, 2025
10 Locations
Remote or Hybrid
Machine Learning • Software
The Role

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 work environment

- Employee stock options

- Best-in-class medical and dental benefits

- Parental Leave top-up

- Professional development budget

- Flexible vacation time to promote a healthy work-life blend


We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability, and any other protected ground of discrimination under applicable human rights legislation. 


CentML strives to respect the dignity and ‎‎independence of people with disabilities and is committed to giving them the same ‎‎opportunity to succeed as all other employees. 


Inclusiveness is core to our culture at CentML, and we strive to ensure you get the most from your interview experience. CentML makes reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to the Talent team.

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The Company
HQ: Toronto, Ontario
50 Employees
Year Founded: 2022

What We Do

We pioneer novel technology to enhance computing efficiency, making AI accessible for innovation and to benefit the global community.

We believe honesty builds integrity, honing craftsmanship delivers excellence, and collaboration fosters community.

Why Work With Us

Our journey began in the esteemed Efficient Computing Systems lab at the University of Toronto, under the leadership of our CEO, Gennady Pekhimenko. Today, the EcoSystems lab stands proudly as one of the world’s foremost authorities in Machine Learning Systems.

Our founding team is made up of experts in AI, ML compilers and ML hardware and has led

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