Apply📍 United States
🧭 Full-Time
💸 140000.0 - 180000.0 USD per year
🔍 Artificial Intelligence, Material Science, Chemistry
- MSc Degree in Computer Science or a related field
- Understanding of machine learning algorithms and techniques
- 3+ years of experience in building and deploying ML systems
- 3+ years of experience working with Python and MLOps tools, including Docker, Kubernetes, KubeFlow, TensorFlow, PyTorch, Sagemaker, MLFlow
- 2+ years of cloud experience (AWS or Azure ML Platforms)
- 3+ years of experience in Software Engineering practices such as version control, testing, DevOps (build pipelines, CI/CD), and Python package management
- Demonstrated ability to communicate complex technical details at a high level effectively
- Design, build, and maintain scalable and resilient MLOPS architecture and code across our platform codebase, Kubernetes/KServe, AWS, and Azure
- Collaborate with Research Scientists and DevOps Engineers to deploy custom models on the platform or as independent services
- Help debug and resolve issues with model or service performance
- Provide oversight/guidance and templates for Research Scientists to self-serve ML deployments for non-production needs
- Deploy data assets and pipelines for model inference endpoints
AWSDockerPythonKubeflowKubernetesMLFlowPyTorchAzureTensorflowCI/CD
Posted about 1 month ago
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