Machine Learning Engineer

About Us We are a fast growing technology company specializing in current and emerging internet, cloud and mobile technologies. Job Description CodelogicX is a pioneering technology company, proudly certified with ISO 9001:2015 and ISO/IEC 27001:2013 standards. We are committed to advancing innovation and delivering state-of-the-art solutions that redefine industry standards. We are seeking a skilled and detail-oriented Core Machine Learning Engineer with a strong foundation in classical machine learning and deep learning techniques. The ideal candidate will have hands-on experience building, evaluating, and optimizing machine learning models, with a focus on core ML concepts rather than generative AI or LLM-based systems. 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 Health insurance Hybrid working mode Provident Fund Parental leave Yearly Bonus Gratuity Location: Kolkata