Job Description
This role focuses on building advanced AI/ML and data science solutions for large-scale business and logistics problems. The engineer works with massive datasets, develops predictive models, deploys machine learning systems, and collaborates with cross-functional teams to create production-ready AI platforms and analytics solutions.
The position combines:
- Data Science
- Machine Learning Engineering
- Data Engineering
- Cloud & DevOps
- Research & Innovation
Location: Chennai
Responsibilities
Data Science & Machine Learning
- Build predictive, prescriptive, and statistical models
- Develop AI/ML solutions using:
- Scikit-learn
- XGBoost
- TensorFlow
- PyTorch
- Spark MLlib
- Solve large-scale business and logistics problems using advanced analytics
- Research and experiment with modern AI techniques
Data Engineering
- Work with large structured and unstructured datasets
- Design reusable data science assets and pipelines
- Scale ML solutions from prototype to production
- Build cluster-scale solutions using distributed systems
Deployment & Production
- Deploy production-grade ML systems
- Use cloud platforms like:
- AWS
- Azure
- Databricks
- Implement CI/CD and DevOps practices
- Maintain reusable codebases and templates
Collaboration
- Work with:
- Business teams
- Software engineers
- Data engineers
- Product stakeholders
- Translate technical insights into business value
- Support cross-functional delivery teams
Innovation & Research
- Stay updated with latest AI/ML trends
- Contribute to R&D initiatives
- Create scalable and reusable AI frameworks
Required Skills
Programming
- Python
- SQL
- Distributed computing concepts
Machine Learning & AI
- Scikit-learn
- TensorFlow
- PyTorch
- XGBoost
- MLlib
- Predictive modeling
- Statistical analysis
Cloud & Platforms
- AWS
- Azure
- Databricks
- MLFlow
Data Engineering
- Spark
- Big data processing
- ETL/data pipelines
Mathematics & Statistics
- Linear Algebra
- Vector Calculus
- Optimization techniques
DevOps & Engineering
- CI/CD
- Agile
- Version control
- Production deployment
Preferred Candidate Profile
Ideal for someone who:
- Has strong AI/ML project experience
- Enjoys solving complex real-world problems
- Can work on both research and production systems
- Has strong mathematical foundations
- Can collaborate across technical and business teams
Experience Level
- Mid-to-Senior Data Scientist
- Suitable for candidates with strong practical ML deployment experience and cloud/data engineering exposure
Main Technologies Mentioned
- Python
- Spark
- Databricks
- TensorFlow
- PyTorch
- XGBoost
- AWS
- Azure
- MLFlow
- CPLEX
- Gurobi