TensorGo - MLOps Engineer (2-4 yrs)

Job Description :

Requirements :

- Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)

- Fluency in Python

- Comfort with Linux administration

- Experience working with cloud computing and database systems

- Experience building custom integrations between cloud-based systems using APIs

- Experience developing and maintaining ML systems built with open source tools

- Experience developing with containers and Kubernetes in cloud computing environments

- Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)

- Ability to translate business needs to technical requirements

- Strong understanding of software testing, benchmarking, and continuous integration

- Exposure to machine learning methodology and best practices

- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)

Responsibilities :

- Design the data pipelines and engineering infrastructure to support enterprise machine learning systems at scale

- Take offline models data scientists build and turn them into a real machine learning production system

- Develop and deploy scalable tools and services to handle machine learning training and inference

- Identify and evaluate new technologies to improve performance, maintainability, and reliability of machine learning systems

- Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.

- Support model development, with an emphasis on auditability, versioning, and data security

- Facilitate the development and deployment of proof-of-concept machine learning systems