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What you will do
Be an influencer and leader in MLOps related open source communities to help build an active MLOps open source ecosystem for Open Data Hub and OpenShift AI
Act as a Model Serving SME within Red Hat by supporting customer facing discussions, presenting at technical conferences, and evangelizing OpenShift AI within the internal community of practices
Architect and design new features in collaboration with open source communities such as KubeFlow and KServe
Contribute to developing and integrating model inference and runtimes in OpenShift AI product
Collaborate with our product management and customer engineering teams to identify and expand product functionalities
Mentor, influence, and coach a team of distributed engineers
What you will bring
Advanced Level knowledge of Python or Golang a MUST
Hands on experience in deploying and maintaining machine learning models in production environments
Ideally work Hybrid in Montreal CA or Toronto CA or be remote Eastern Time Zone
Solid understanding of the fundamentals of model inferencing and runtimes architectures
Advanced level knowledge and experience with development in Go, and Python
Strong experience with Kubernetes
Excellent written and verbal communication skills; fluent English language skills
The following will be considered a plus:
Bachelor's degree in statistics, mathematics, computer science, operations research, or a related quantitative field, or equivalent expertise; Master’s or PhD is a big plus
Experience in engineering, consulting or another field related to model serving and monitoring, model registry, deep neural networks, in a customer environment or supporting a data science team
Familiarity with popular python machine learning libraries such as PyTorch, Tensorflow, and Hugging Face
Experience with monitoring and alerting tools such as Prometheus
The salary range for this position is $111,260 - $183,530. Actual offer will be based on your qualifications.
Posting date5 days ago(4/1/2024 2:51 PM)
Software Engineering
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