Mlops Engineer

Location - Noida UP / Gurugram HR / Pune MH (3 days hybrid / week) Experience : 6-12 years

Shift Timing : 1 : 00 PM to 10 : 00 PM

Major Skills : ML OPS, ML Ops frameworks like Kubeflow , MLflow , TensorFlow Extended (TFX) , KubeFlow Pipelines, AWS Cloud, CI / CD pipeline, containerization (Docker) and orchestration (Kubernetes)

Job Description

6+ years of experience in ML Ops engineering or a related field.

Strong proficiency in Python, with experience in machine learning libraries such as TensorFlow, PyTorch, scikit-learn, etc.

Extensive experience with ML Ops frameworks like Kubeflow, MLflow, TensorFlow Extended (TFX), KubeFlow Pipelines, or similar.

Strong experience in deploying and managing machine learning models in cloud environments (AWS, GCP, Azure).

Proficiency in managing CI / CD pipelines for ML workflows using tools such as Jenkins, GitLab, CircleCI, etc.

Hands-on experience with containerization (Docker) and orchestration (Kubernetes) technologies for model deployment.

• Skills : SageMaker, PySpark, AWS Services ;

Nice to have : MLOps

Job In

Experience Required (Min) - 6

Experience Required (Max) - 8

Primary Skill - Data Science and Machine Learning - Data Science and Machine Learning - AI / ML

Employee Class - Permanent