Machine Learning Engineer

2 days ago

Nadiad, India TalentBridge Full time

Job Summary: As a Machine Learning Engineer specializing in generative AI, you will be responsible for designing, developing, and deploying advanced machine learning models that generate high-quality, human-like content. You will collaborate with cross-functional teams to integrate these models into our products, enhancing their capabilities and delivering exceptional value to our clients. Key Responsibilities: - Develop, train, and optimize generative AI models for various applications, including text, image, and audio generation. - Collaborate with product managers, software engineers, and data scientists to understand project requirements and deliver robust AI solutions. - Conduct research to stay updated on the latest advancements in generative AI and apply best practices to improve model performance. - Implement and maintain scalable machine learning pipelines for training and deploying models in production environments. - Evaluate and fine-tune models to ensure they meet performance, accuracy, and efficiency standards. - Perform data preprocessing, augmentation, and annotation to prepare high-quality datasets for model training. - Troubleshoot and resolve issues related to model performance, data quality, and integration with other systems. - Document model architecture, training processes, and performance metrics for internal and client-facing reports. Qualifications: - Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. - Proven experience in developing and deploying generative AI models using frameworks such as TensorFlow, PyTorch, or similar. - Strong programming skills in Python and proficiency with machine learning libraries and tools. - Familiarity with natural language processing (NLP), computer vision, and other relevant AI techniques. - Experience with cloud platforms such as AWS, Google Cloud, or Azure for model deployment and management. - Knowledge of data preprocessing, feature engineering, and model evaluation techniques. - Excellent problem-solving skills and the ability to work independently and as part of a team. - Strong communication skills to effectively convey technical concepts to non-technical stakeholders. Preferred Qualifications: - Experience with GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other advanced generative models. - Understanding of ethical considerations and bias mitigation in AI systems. - Contributions to open-source projects or publications in relevant conferences/journals. - Experience with MLOps practices and tools for continuous integration and deployment of machine learning models.

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