Machine Learning Engineer

You will be working as a Machine Learning Engineer in an in-office setting in Hyderabad. Your primary focus will be on utilizing AI/ML techniques, specifically in computer vision applications. Your responsibilities will include designing, building, and fine-tuning machine learning models for tasks like object detection, segmentation, and image classification. As a Machine Learning Engineer, you will leverage pre-trained models and implement fine-tuning to customize them for specific use cases. It will be crucial for you to optimize model performance by incorporating cutting-edge techniques in transfer learning, regularization, and hyperparameter tuning. Collaboration with data scientists, engineers, and product teams is essential to deliver AI solutions that align with business requirements. Your role will involve developing scalable solutions and deployment pipelines to operationalize machine learning models effectively. You will need to prioritize model efficiency, ensuring high speed and low latency in production environments. Staying updated on the latest trends and technologies in AI, machine learning, and computer vision will be key in enhancing existing solutions. Additionally, you will conduct thorough evaluations of models using relevant metrics and implement strategies for performance enhancement. Troubleshooting and resolving model-related issues in production environments will also be part of your responsibilities. To qualify for this role, you should hold a Bachelor's, Master's, or PhD in Computer Science and possess at least 3 years of experience in machine learning or deep learning, focusing on computer vision. Expertise in model fine-tuning, transfer learning, and working with pre-trained models like ResNet, VGG, and EfficientNet is required. Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Keras, along with a deep understanding of deep learning architectures, is essential. Familiarity with vision-specific tasks, data preprocessing, augmentation, and labeling techniques for vision tasks, as well as proficiency in programming languages like Python, C++, or similar, are necessary. A strong grasp of model evaluation techniques and metrics for computer vision tasks and experience with cloud platforms and containerization technologies will be advantageous.,