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