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Machine Learning Engineer
4 weeks ago
Role: ML Engineer Job Type: In-office (Hyderabad)
We are seeking a Machine Learning Engineer with a strong background in AI/ML techniques and expertise in computer vision.
The ideal candidate will have experience with model fine-tuning, working with pre-trained models, and deploying machine learning solutions at scale.
Key Responsibilities:- Design, build, and fine-tune machine learning models for computer vision applications, such as object detection, segmentation, image classification, and scene understanding.
- Leverage pre-trained models (e.g., CNNs, transformers, YOLO, etc.) and perform fine-tuning to adapt them to specific use cases.
- Optimize model performance by implementing cutting-edge techniques in transfer learning, regularization, and hyperparameter tuning.
- Work closely with data scientists, engineers, and product teams to deliver AI solutions that meet business requirements.
- Develop scalable solutions and deployment pipelines to operationalize machine learning models.
- Maintain a strong focus on the efficiency of models, ensuring high speed and low latency in production environments.
- Stay up-to-date with the latest trends and technologies in AI, machine learning, and computer vision, applying this knowledge to improve existing solutions.
- Conduct rigorous evaluation of models using relevant metrics and implement strategies for performance improvement.
- Troubleshoot and resolve model-related issues in production environments.
- Bachelor's/Master's/PhD in Computer Science
- 3+ years of experience in machine learning or deep learning, with a focus on computer vision.
- Expertise in model fine-tuning, transfer learning, and working with pre-trained models (e.g., ResNet, VGG, EfficientNet, etc.).
- Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, Keras, or similar.
- In-depth understanding of deep learning architectures (e.g., CNNs, RNNs, transformers).
- Familiarity with vision-specific tasks such as image classification, object detection, semantic segmentation, and image generation.
- Hands-on experience with training large models and optimizing them for performance and resource constraints.
- Knowledge of data preprocessing, augmentation, and labeling techniques for vision tasks.
- Proficiency in programming languages such as Python, C++, or similar.
- Strong understanding of model evaluation techniques and metrics for computer vision tasks (e.g., mAP, IoU, AUC).
- Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies like Docker is a plus.
