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AI/ML Engineer

Persistent

Hyderabad

8-12 years

Today

$44.6K–62.7K/yr

Full time

Onsite

Skills Required Machine Learning

NLP

Sentiment Analysis

Topic Modeling

TF-IDF

VADER Sentiment

MLflow

Kubeflow

Apache Airflow

Vertex AI

Dataiku

GCP

AWS

Azure

Python

Description Persistent is an AI-led Digital Engineering and Enterprise Modernization partner seeking an experienced AI/ML Engineer for their MLOps team to deploy and maintain machine learning solutions in production.

Company: Persistent

Role: ML Ops

Location: Pune/Hyderabad

Experience

- 8 to 12 years overall IT experience
- At least 3 years of hands-on AI/ML engineering experience

Responsibilities

- Collaborate with Data Science and Engineering teams to deploy, operationalize, and scale machine learning models in production
- Design, develop, and maintain end-to-end MLOps pipelines for model training, validation, deployment, monitoring, and retraining
- Operationalize complex machine learning models and algorithms ensuring reliability, scalability, and performance
- Develop and maintain adaptable data pipelines to support use-case-specific data requirements
- Integrate AI/ML solutions into business workflows and collaborate with upstream and downstream teams
- Build and maintain automated pipelines for generating and publishing model performance metrics
- Monitor model health, performance, data quality, and model drift and implement remediation strategies
- Develop operational runbooks, support procedures, and maintenance guidelines for production ML solutions
- Participate in troubleshooting, root cause analysis, and continuous improvement of ML platforms and pipelines

Additional Responsibilities





- Support procedures and maintenance guidelines for production ML solutions
- Troubleshooting and root cause analysis of ML platforms and pipelines

Nice To Have

- Experience with Vertex AI or Dataiku
- Exposure to MLOps tools and frameworks such as MLflow, Kubeflow, Airflow
- Experience with cloud platforms such as GCP, AWS, or Azure
- Knowledge of CI/CD automation for ML deployments
- Experience with model governance, risk oversight, and compliance processes

More Skills SQL, Machine learning model deployment, Data pipelines, MLOps practices, Regression, Classification, Model evaluation and performance measurement, Natural Language Processing (NLP), Scikit-Learn, Pandas, PySpark, ETL/ELT workflows, Model monitoring, Performance tracking, Model lifecycle management, Cloud-based AI/ML platforms, Distributed data processing environments, CI/CD automation for ML deployments, Model governance, Risk oversight, Compliance processes

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