- Location: Coimbatore
- Work Mode: On-site
- Experience: 1 – 1.5 Years
- Role Overview
We are looking for a Machine Learning Engineer with early experience in building end-to-end ML solutions for data-driven decision-making. The role involves working across the ML lifecycle, including data processing, model development, deployment, and performance monitoring. The candidate will collaborate with cross-functional teams to deliver scalable and reliable machine learning systems.
- Key Responsibilities
- Develop and implement machine learning models using appropriate algorithms and techniques
- Perform exploratory data analysis (EDA) and data preprocessing
- Conduct feature engineering and model selection for optimal performance
- Train, validate, and fine-tune machine learning models
- Deploy machine learning models in production environments (cloud or on-premises)
- Monitor model performance and implement improvements or retraining strategies
- Work with large datasets using distributed computing frameworks
- Conduct A/B testing and evaluate different model architectures
- Implement time series models for forecasting and predictive analysis
- Collaborate with data engineers and software teams for integration
- Maintain documentation for models, experiments, and workflows
- Ensure scalability, reliability, and performance of ML systems
- Required Qualifications
- Bachelor’s degree in Computer Science, Electronics, Data Science, or related field
- 1–1.5 years of hands-on experience in machine learning or data science
- Experience working on end-to-end ML projects (academic or industry)
- Understanding of statistical modeling and machine learning fundamentals
- Technical Skills
Programming & Libraries
- Python (NumPy, Pandas, Scikit-learn)
Machine Learning Frameworks
- TensorFlow, PyTorch, Keras
Machine Learning Concepts
- Supervised and Unsupervised Learning
- Reinforcement Learning (basic understanding)
- Model evaluation and hyperparameter tuning
Data Engineering & Big Data
Data Analysis & Visualization
- Matplotlib, Seaborn, Tableau, Power BI
Specialized Areas
- Time Series Analysis and Forecasting
- A/B Testing and Experimentation
Deployment & Infrastructure
- Model deployment (cloud platforms or on-premises systems)
- Good to Have (Optional)
- Experience with containerization (Docker)
- Exposure to Kubernetes or MLOps practices
- Experience with real-time data processing pipelines
- Knowledge of version control systems (Git)
- Exposure to cloud platforms (AWS / Azure / GCP)