Job Title: Machine Learning Engineer
Job Summary:
We are seeking a Fresher Machine Learning Engineer to assist in developing, training, and deploying machine learning models for real-world applications. The ideal candidate should have a strong foundation in Python, data preprocessing, model training, and AI algorithms. This role involves data analysis, model experimentation, and working with AI frameworks to build intelligent systems.
Key Responsibilities:
- Assist in collecting, cleaning, and preprocessing datasets for machine learning models
- Develop and train basic machine learning models using frameworks like TensorFlow, PyTorch, and Scikit-learn
- Implement and evaluate classification, regression, clustering, and deep learning models
- Perform feature engineering and data transformation to improve model accuracy
- Work with supervised and unsupervised learning techniques to solve business problems
- Optimize model performance and hyperparameters using techniques like GridSearchCV and cross-validation
- Deploy machine learning models using Flask, FastAPI, or cloud-based solutions (AWS, Google Cloud, Azure)
- Work with Jupyter Notebooks, Pandas, NumPy, and Matplotlib for data visualization and analysis
- Assist in documenting and explaining ML models, results, and performance metrics
- Stay updated on latest AI trends, algorithms, and best practices
Skills and Knowledge Required:
- Proficiency in Python and familiarity with ML libraries (Scikit-learn, TensorFlow, PyTorch)
- Basic understanding of machine learning algorithms, including regression, classification, and clustering
- Knowledge of data preprocessing techniques, feature engineering, and handling missing values
- Hands-on experience with data manipulation using Pandas and NumPy
- Familiarity with basic deep learning architectures (CNNs, RNNs, Transformers) (optional)
- Understanding of statistics, probability, and linear algebra for ML model development
- Basic knowledge of model evaluation metrics (accuracy, precision, recall, F1-score, RMSE)
- Experience with visualization tools (Matplotlib, Seaborn)
- Exposure to cloud-based ML tools (AWS SageMaker, Google AI Platform, Azure ML) (optional)
- Strong analytical and problem-solving skills
Educational Qualifications:
- Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field
- Certifications in Machine Learning, AI, or Data Science (Coursera, Udacity, AWS, Google ML) are a plus
Experience:
- 0-1 year of experience in machine learning, AI model development, or data science projects
- Academic projects, internships, or Kaggle competitions are highly preferred
Key Focus Areas:
- Data Collection, Cleaning & Preprocessing
- Supervised & Unsupervised Learning Models
- Model Training & Performance Optimization
- Deployment of ML Models
Tools and Technologies:
- Programming Languages: Python
- ML Frameworks: Scikit-learn, TensorFlow, PyTorch, Keras
- Data Processing & Visualization: Pandas, NumPy, Matplotlib, Seaborn
- Development Tools: Jupyter Notebook, Google Colab
- Model Deployment: Flask, FastAPI, Docker (optional)
- Cloud Services (Optional): AWS SageMaker, Google Cloud AI, Azure ML
Other Requirements:
- Eagerness to learn and apply new ML techniques
- Ability to work independently and as part of a team
- Passion for AI, machine learning, and real-world problem-solving
- Strong communication and documentation skills