| ML Lead Engineer || Full Onsite || MN WA IL CA || NO H1B CPT OPT at Remote, Remote, USA |
| Email: [email protected] |
| From: Awkash Kumar, Largeton INC [email protected] Reply to: [email protected] JD :: Mandatory Skills: - 3-5 years experience working with MLOps system - Must have Healthcare industry experience - 3-5 years of experience in developing/working on MLOps systems, and an overall experience of 10+years into Data Science - Expert on using Python to develop scripts for MLOps - Expert on cloud platform (Azure/AWS) developer environments Requirements Experience in - Designing data pipelines and engineering infrastructure to support enterprise machine learning systems at scale - Organizing offline models that data scientists build and turn them into a real machine learning production system - Developing and deploying scalable tools and services for our clients to handle machine learning training and inference - Understanding application of software engineering rigor and best practices to machine learning, like CI/CD, automation, auditability, versioning, and data security (KubeFlow, MLFlow) - Developing and maintaining ML systems built with open source tools (Kale) - Facilitate the development and deployment of proof-of-concept machine learning systems - Previous work with data drift model drift - Expertise on Kubernetes, Kafka, and/or docker - Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.) - Expert in using AWS or Azure ML tools (SageMaker/Azure ML etc.) [preferred] Keywords: continuous integration continuous deployment machine learning ML Lead Engineer || Full Onsite || MN WA IL CA || NO H1B CPT OPT [email protected] |
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| Tue Jul 30 00:02:00 UTC 2024 |