TensorGo Software - DevOps/MLOps Engineer (3-5 yrs)

Profile :



We are looking for an experienced and high-energy ML Ops Engineer. The primary function of this role is to design enterprise architecture. Envision and drive solution architecture after hearing the product s vision and user stories with ability to envision and drive a proactive architectural roadmap for an existing product keeping in mind the future requirements.

Requirements :

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

- Hands-on expertise in Python and ML frameworks.

- Expertise 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.

- Experience with Prometheus and Grafana integrations for highly scalable environments.

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.