DevOps Engineer

Job Title: · DevOps Engineer

Requirement: 1

Experience: 3 to 6

Location: Andheri East

Job Type: Permanent

Work Mode: On-site (Work from Office)

Work Schedule: 5 days a week (Monday to Friday)

Weekends Off: Saturday and Sunday

Shift Timings: 09:30 AM to 06:30 PM (with flexible start time, up to 10:30 AM)

Key Responsibilities

1.Provide deep expertise to help steer scalability and stability improvements early in the life-cycle of machine learning development while working with the rest of the team to automate existing processes that deploy, test, and lead our production environments.

2. Orchestrate systems using Kubernetes.

3. Set up CI/CD pipelines of multiple applications.

4. Lead the conversation on architecting solutions to machine learning specific needs relating to deployment, systems architecture, and other tools and automation that ensure the reliability of machine learning products and simplify Deep Learning Engineer workflows.

5. Lead by example and evangelize DevOps best practices within other data science and engineering teams.

6. Work with deep learning engineers and DevOps teams to troubleshoot server/infrastructure/systems-level issues.

7.Mentor and enable ML engineers to perform basic DevOps functions.

8. Have the freedom to suggest and drive organization-wide initiatives while being part of providing the technical vision and strategy.

9. Build, test, and maintain the infrastructure and tools to allow for the speedy development and release of the software.

10. Manage massive complex datasets, detect patterns and antipatterns, uncover new insights, iterate and refine queries.

11. Enable Model tracking model experimentation, Model automation.

12. Develop scalable ML pipelines.

13. Build the knowledge base required to deliver increasingly complex MLOPS projects on the Cloud(AWS)/On Premises server.

14. Sound Knowledge of Git for Source code management.

15. Need to  Know about Host Restful,FlaskAPI with Nginx, Apache with Gunicorn service.

16. Basic Knowledge of MLOps, machine learning and docker, Kubernetes.

17. Database programming using any SQL flavor (MySQL, PostgreSQL).

18. Sound Knowledge Linux,Ubuntu ,Windows Environment.

19. Host All Python Flask APIs with the IIS Server.

20• Familiar with data science libraries like Pandas, scikit-learn, Pytorch and Open-CV, onxx runtime.

21• Hunger and passion for learning new skills.