MLOpsEngineer (LLMMLOps)

Start Date

Starts Immediately

CTC (ANNUAL)

Competitive salary Market-competitive salary

Experience

4 year(s)

4 year(s)

Apply By

Not Provided

Posted today

Job

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About the job

Experience-4+yrs

Key Responsibilities

- Model Deployment using Docker and Kubernetes.
- Design, build, and maintain CI/CD pipelines for ML workflows.
- Monitor model drift, latency, and performance metrics.
- Manage cloud infrastructure across AWS, Azure, or GCP.
- Collaborate with Data Scientists to optimise model performance and scalability.

Required Skills

- Strong proficiency in Python and Shell Scripting.
- Hands-on experience with Docker, Kubernetes, and CI/CD tools.
- Experience with TensorFlow, PyTorch, and Scikit-Learn.
- Knowledge of MLflow and Weights & Biases.
- Exposure to AWS SageMaker, Azure Machine Learning, or GCP Vertex AI.
- Good understanding of MLOps, DevOps, and ML deployment best practices.





Earn certifications in these skills

+ 6 more skills

Who can apply

Only those candidates can apply who:

1. have minimum 4 years of experience

Salary

Probation:

Duration:

Salary during probation:

After probation:

Annual CTC: Competitive salary

Number of openings

1

Editor’s note

Information above is Internshala's interpretation and paraphrasing of what we found on the shared link.

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📌 MLOpsEngineer (LLMMLOps) (WFH)
🏢 Capabiliq
📍 India