Machine Learning Engineer

Roles & Responsibilities :

• · Design, develop, and deploy machine learning models using core ML techniques .
• · Implement supervised and unsupervised learning algorithms for structured and unstructured data .
• · Work on end-to-end ML pipelines including data preprocessing, feature engineering, model training, and evaluation .
• · Apply deep learning models for tasks such as image classification and object detection .
• · Analyze datasets to extract meaningful insights and improve model performance .
• · Perform data cleaning, transformation, and feature selection to enhance model accuracy .
• · Evaluate model performance using appropriate metrics and validation techniques .
• · Optimize models for performance, scalability, and efficiency .
• · Collaborate with cross-functional teams including data engineers and software developers .
• · Document experiments, workflows, and model performance results .

Requirements

• · Minimum 3 years of hands on experience in core machine learning.
• · Technical skills: Strong proficiency in Scikit-learn , PyTorch , NumPy , Pandas , OpenCV , Matplotlib , EAI Library (or similar ML frameworks)
• · Machine Learning Algorithms: - Supervised Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forest . - Unsupervised Learning: Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transformer Architecture, Object Detection, Image Classification .
• · Deep Learning: Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transformer Architecture, Object Detection, Image Classification
• Core ML Knowledge: Data Cleaning and Preprocessing, Feature Engineering, Model Evaluation Techniques (e.g., cross-validation, metrics analysis).

Benefits