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ML Pipeline Engineer

ML Pipeline Engineer

ti Steps

0 - 3 years

2 - 4 Lacs

hyderabad chennai bengaluru

Posted:8 hours ago| Platform:

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Skills Required

microsoft flow deployment deploying models ml algorithms machine learning aws sagemaker ml deployment devops python ml

Work Mode

Work from Office

Job Type

Full Time

Job Description

About the Role:

ML Pipeline Engineer

Key Responsibilities:

Pipeline Development & Deployment

Design and implement end-to-end ML pipelines for training, validation, deployment, and monitoring.
Automate data ingestion, preprocessing, feature engineering, model training, evaluation, and serving.
Enable reproducible and modular workflows using tools like MLflow, Kubeflow, or TFX.

Model Serving & Infrastructure

Develop scalable model serving architectures (batch, real-time, streaming).
Build infrastructure for model versioning, A/B testing, canary deployments, and rollbacks.
Integrate with cloud platforms (AWS, GCP, Azure) and container orchestration systems (Kubernetes, Docker).

Monitoring & Performance Optimization

Implement monitoring for model drift, performance degradation, and data quality issues.
Build logging and alerting systems to ensure reliability of ML services.

Preferred Qualifications:

Experience deploying models at scale in production environments.
Knowledge of data versioning tools (DVC, LakeFS).
Familiarity with distributed data processing (Spark, Dask, Ray).
Exposure to model monitoring tools (Evidently, WhyLabs, Prometheus).
Experience with real-time ML pipelines (Kafka, Flink, etc.).

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