Posted Apr 4, 2026
As a Machine Learning Engineer at HDIP, your role involves leveraging your expertise in computer vision and deep learning to develop and implement real-world AI solutions. You will be responsible for a range of tasks including designing and developing CV models, optimizing deep learning architectures, building scalable ML models, and collaborating with cross-functional teams. Key Responsibilities:
Design and develop CV models for detection, classification, tracking, OCR, and segmentation. - Implement and optimize deep learning architectures such as CNNs, transformers, and vision models. - Build scalable ML models for various business use cases. - Deploy inference pipelines for real-time or batch processing. - Evaluate new CV/DL techniques, perform model optimization, and benchmarking. - Collaborate with data engineers to build pipelines for ETL, labeling, and feature extraction. - Partner closely with Product, Engineering, and Domain stakeholders to translate business requirements into technical solutions. Qualifications Required:
3-8 years of ML/CV/AI engineering experience. - Strong hands-on coding skills in Python and DL frameworks like PyTorch, TensorFlow, Keras, and OpenCV. - Expertise in CV tasks such as Object Detection, Segmentation, Keypoint Detection, OCR, and Tracking. - Exposure to state-of-the-art architectures like CNNs, EfficientNet, ViTs, Transformers, and LLM-based vision models. - Understanding of ML fundamentals including statistics, probability, optimization, and feature engineering. - Experience with MLOps/cloud platforms like AWS/GCP/Azure, Docker, K8s, MLflow/Kubeflow (preferred). Key Responsibilities:
Design and develop CV models for detection, classification, tracking, OCR, and segmentation. - Implement and optimize deep learning architectures such as CNNs, transformers, and vision models. - Build scalable ML models for various business use cases. - Deploy inference pipelines for real-time or batch processing. - Evaluate new CV/DL techniques, perform model optimization, and benchmarking. - Collaborate with data engineers to build pipelines for ETL, labeling, and feature extraction. - Partner closely with Product, Engineering, and Domain stakeholders to translate business requirements into technical solutions. Qualifications Required:
3-8 years of ML/CV/AI engineering experience. - Strong hands-on coding skills in Python and DL frameworks like PyTorch, TensorFlow, Keras, and OpenCV. - Expertise in CV tasks such as Object Detection, Segmentation, Keypoint Detection, OCR, and Tracking. - Exposure to state-of-the-art architectures like CNNs, EfficientNet, ViTs, Transformers, and LLM-based vision models. - Understanding of ML fundamentals including statistics, probability, optimization, and feature engineering. - Experience with MLOps/cloud platforms like AWS/GCP/Azure, Docker, K8s, MLflow/Kubeflow (preferred).
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