Cenergy International Services
Website:
cenergyintl.com
Job details:
Machine Learning Engineer
Location: Bengaluru (Work from Office)
Work Mode: Monday WFH | Tuesday–Friday WFO
Shift: 01:30 PM – 10:30 PM
Contract Duration: 6 Months contract with extension
Role Summary
We are looking for a Machine Learning Engineer with strong hands-on experience in building, deploying, and maintaining machine learning models in production environments. The role involves working on predictive analytics, time-series forecasting, and anomaly detection solutions to support business and operational decision-making.
Key Responsibilities
- Design, develop, and deploy machine learning models for real-world business use cases
- Work on predictive analytics, time-series forecasting, and anomaly detection
- Gather and analyze requirements, and translate them into scalable ML solutions
- Perform data exploration, feature engineering, feature selection, and model tuning
- Build and optimize models using frameworks like Scikit-learn, TensorFlow, PyTorch, or XGBoost
- Deploy models using Azure Machine Learning and integrate them into applications and data pipelines
- Work with Azure Databricks for large-scale data processing and model training
- Implement MLOps practices including CI/CD, model versioning, monitoring, and retraining
- Conduct testing, validation, and performance optimization of models
- Collaborate with data engineers, architects, and business teams to deliver end-to-end solutions
- Troubleshoot production issues and enhance existing models
Required Skills & Experience
- 5–7 years of experience in Machine Learning / Applied AI roles
- Strong programming skills in Python
- Hands-on experience with:
- Scikit-learn, TensorFlow, PyTorch, XGBoost
- Solid experience in:
- Predictive modeling
- Time-series forecasting
- Anomaly detection techniques
- Experience with Azure Machine Learning (AML) for model development and deployment
- Strong exposure to Azure Databricks
- Experience working with large datasets, including time-series or sensor data
- Good understanding of:
- Feature engineering
- Model evaluation and optimization
- Hyperparameter tuning
- Experience implementing MLOps practices (CI/CD, monitoring, lifecycle management)
- Strong problem-solving and debugging skills
- Experience working in Agile environments
Good to Have
- Experience with industrial or operational data (manufacturing, energy, utilities, etc.)
- Exposure to PI Historian or similar systems
- Understanding of prescriptive analytics or optimization techniques
- Experience working with OT (Operational Technology) data
- Experience building AI/ML solutions on Azure cloud at scale
Education
- Bachelor’s degree in Computer Science, Engineering, or a related technical field
Ideal Candidate Profile
- Strong hands-on ML engineer (not just theoretical knowledge)
- Experience deploying models into production
- Comfortable working with large datasets and real-world problems
- Able to work independently while collaborating with cross-functional teams.
Click on Apply to know more.
