Position Summary

We are seeking a highly motivated Machine Learning Engineer (MLE) to design, develop, deploy, and operationalize machine learning solutions leveraging industrial and enterprise data. The ideal candidate will possess robust expertise in machine learning model development, time-series analytics, MLOps, and cloud-based data platforms.

This role will focus on building predictive and prescriptive analytics solutions using operational data from platforms such as AVEVA/OSI PI System, Azure Data Explorer (ADX), Databricks ML, and DataRobot. The candidate will collaborate with Data Scientists, Data Engineers, Product Owners, and Business SMEs to deliver scalable AI/ML solutions that drive operational excellence and business value.

Experience: 4–8 Years

Location: Bengaluru, India (Hybrid)

Key Responsibilities

Machine Learning Development

- Design, develop, train, evaluate, and validate machine learning models for forecasting, anomaly detection, predictive maintenance, asset performance optimization, and classification/regression use cases.
- Develop feature engineering, data preparation, and model training pipelines using Python-based ML frameworks.
- Analyze large-scale operational and industrial datasets to identify patterns, trends, and actionable insights.
- Perform model tuning, hyperparameter optimization, and performance benchmarking.

Time-Series Analytics

- Work extensively with time-series and sensor data sourced from AVEVA PI System (OSI PI) and Azure Data Explorer (ADX).
- Develop forecasting and anomaly detection models for industrial operations.
- Build scalable analytics workflows for high-frequency telemetry and operational data.

MLOps & Model Lifecycle Management

- Implement MLOps frameworks and best practices for model deployment, monitoring, governance, and lifecycle management.
- Develop automated model training, testing, validation,



and deployment pipelines.
- Monitor model performance, data drift, and model drift in production environments.
- Support model retraining and continuous improvement processes.

Required Qualifications

- bachelor's or master's degree in computer science, Data Science, Artificial Intelligence, Engineering, Statistics, Mathematics, or related discipline.
- 4–8 years of hands-on experience developing and deploying machine learning solutions.
- Strong programming skills in Python and SQL.
- Hands-on experience with DataRobot and Databricks Machine Learning.
- Experience with AVEVA PI System (OSI PI) and Azure Data Explorer (ADX).
- Strong understanding of supervised and unsupervised learning, time-series forecasting, feature engineering, model validation, and statistical analysis.
- Experience implementing MLOps practices including model deployment, monitoring, versioning, and lifecycle management.

Preferred Certifications

- Microsoft Certified: Azure Data Scientist Associate (DP-100)
- Microsoft Certified: Azure AI Engineer Associate (AI-102)
- Databricks Certified Machine Learning Professional
- DataRobot AI Practitioner Certification

Company Description

Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients' businesses through designing the products and services their customers truly value.

📌 Machine Learning Engineer (Bengaluru)
🏢 Publicis Sapient
📍 Bengaluru