ML Engineer

Role Overview: As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models that utilize Computer Vision and Generative AI techniques. Your main focus will be on building and enhancing AI systems to address real-world challenges and contribute to the innovation of products and services. Key Responsibilities: - Utilize machine learning frameworks like TensorFlow, PyTorch, Keras, or similar to develop models - Implement Computer Vision techniques including image classification, object detection, segmentation, and tracking - Work with Generative AI models such as GANs, VAEs, and other deep learning-based generative models - Utilize computer vision libraries such as OpenCV, scikit-image, or similar - Apply model optimization techniques like pruning, quantization, and knowledge distillation - Utilize strong programming skills in Python for data manipulation, model training, and evaluation - Collaborate with cross-functional teams to explain complex AI concepts clearly Qualifications Required: - 2-5 years of hands-on experience in machine learning engineering with a focus on Computer Vision and Generative AI - Strong knowledge of machine learning frameworks such as TensorFlow, PyTorch, Keras, or similar - Expertise in Computer Vision techniques and Generative AI models - Solid understanding of computer vision libraries such as OpenCV, scikit-image, or similar - Experience with model optimization techniques and strong programming skills in Python - Familiarity with DevOps practices related to machine learning and cloud platforms - Knowledge of NLP, Deep Learning, and other AI fields - Experience with deploying models to production and managing model lifecycle - Excellent problem-solving skills and analytical thinking, along with a passion for innovation - Strong communication skills to collaborate effectively with cross-functional teams,