Address
Form of workDo you want to be part of a team that is focused on scaling the deployment, prompt-tuning, and monitoring of Foundation Models and Large Language Models (LLMs)? The OpenShift AI team is looking for a Senior Software Engineer with Kubernetes and Machine Learning experience to join our rapidly growing engineering team. Our team's focus is to make Machine Learning model deployment and monitoring seamless and scalable across the hybrid cloud and the edge. This is a very exciting opportunity to build and impact the next generation of hybrid cloud MLOps platforms.
In this role, you'll be contributing as a technical expert for the model serving and inference runtimes features of the open source Open Data Hub project and OpenShift AI by actively participating in KServe, Kubeflow, HuggingFace, vLLM, and several other open source communities. You will work as part of an evolving development team to rapidly design, secure, build, test and release model serving, trustworthy AI, and model registry capabilities. The role is primarily an individual contributor who will be a key notable contributor to the MLOps upstream communities and collaborate closely with the internal cross-functional development teams.
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
- Advanced Python or Golang experience.
Hands on experience in deploying and maintaining Machine Learning models in production environments
- Ideally work Hybrid in Raleigh or be remote Eastern Time Zone
Solid understanding of the fundamentals of model inferencing and runtimes architectures
Solid understanding of 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.
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Employment Type: OTHER
