Machine Learning Engineer

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