Machine Learning Ops Engineer

What role you will play in team: You will be a critical member of our team focused on automating and streamlining our machine learning workflows. You will work with Data Scientists and Engineers to improve the efficiency and reliability of our ML models.

What you will do: You will design, develop, and maintain infrastructure for training and deploying machine learning models. You will also develop and implement monitoring and alerting systems.

Key responsibility:

• Design, develop, and maintain infrastructure for training and deploying machine learning models.
• Develop and implement CI/CD pipelines for machine learning workflows.
• Develop and maintain monitoring and alerting systems for model performance.
• Collaborate with Data Scientists and Engineers to improve the efficiency and reliability of our ML models.
• Automate machine learning workflows.
• Stay up-to-date on the latest MLOps technologies.

Required Qualification and Skills:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Experience with containerization technologies (e.g., Docker, Kubernetes).
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI).
• Strong scripting skills (e.g., Python, Bash).
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch).

Benefits Included:

• Competitive salary and benefits.
• Opportunity to work on challenging and rewarding projects.
• Collaborative and supportive work environment.
• Opportunities for professional development.
• Flexible work arrangements.

A Day in the Life: A typical day may involve working on CI/CD pipelines, troubleshooting infrastructure issues, collaborating with other teams, and automating machine learning workflows.