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Job Location: Texas
Job Detail:
Lead ML Engineer
Overview:
The ideal candidate is a seasoned ML/Ops engineer with hands on experience in building and maintaining ML pipelines, integrating them with heterogeneous data sources. Good understanding of ML training and serving infrastructure is a must, with an emphasis on secure interoperability of ML services in a multi-service environment. The person should have strong development and communication skills, with an appreciation of data security and continuous integration.
Job Description:
Architect, design and maintain large scale ML pipelines in the Azure/MLFLow/Kubeflow environment.
Model Deployment:- Work with Data Scientists and Infrastructure Engineers to develop and deploy ML models in a data and computationally efficient way. Develop and improve tooling related to system reliability model performance monitoring.
Data Source Integration:
o Integrate ML pipelines with diverse data sources, with data modalities including text and image and audio data, and storage modalities ranging from on-disk files, through databases to internal and web-service APIs.
Presentation and Visualization- Create and share architecture and design documents with the team.
- Create dashboards for performance monitoring.
Qualifications:
- Bachelors or Masters in Computer Science.
- Comprehensive familiarity with common ML service architectures.
- +5 years of professional experience in ML ops involving major cloud platforms.
- Extensive Experience with building ML pipelines utilizing heterogeneous data.
- Good hands-on experience with KubeFlow and MLFlow
- Extensive familiarity with CI, build and source control tools
- Strong communication and project management skills
Ideally the candidate will have:
- +5 years of experience with ML pipeline development in the Azure, AWS or Google Cloud platforms
- +5 years of experience with ML frameworks and tools (scikit-learn, pytorch, tensorflow, etc)
- Hands-on experience data processing tools related to text, images and audio (e.g., OpenCV, Wave2letter++)
- Strong familiarity with development on Linux
- Strong software development skills, with an emphasis on Python
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