Responsible AI Engineer

Project Role : Responsible AI Engineer
Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved.
Must have skills : Computer Vision
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As an AI / ML Engineer, you will develop applications and systems that utilize AI to improve performance and efficiency. Your typical day will involve working on deep learning, neural networks, chatbots, and natural language processing to create innovative solutions. Roles & Responsibilities: - Design and develop computer vision algorithms and models using deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). - Collaborate with cross-functional teams to integrate computer vision solutions into larger AI systems, including chatbots and natural language processing. - Optimize computer vision models for performance and efficiency, utilizing techniques such as pruning, quantization, and compression. - Stay up-to-date with the latest advancements in computer vision and AI, integrating innovative approaches for sustained competitive advantage. - Communicate technical findings effectively to stakeholders, utilizing data visualization tools for clarity. - Expected to be an SME, collaborate and manage the team to perform. Professional & Technical Skills: - Must To Have Skills: Strong proficiency in computer vision techniques and deep learning frameworks such as TensorFlow, PyTorch, and Keras. - Good To Have Skills: Experience with chatbots and natural language processing. - Solid understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, reinforcement learning, and transfer learning. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. - Experience with data preprocessing and augmentation techniques, including image cropping, resizing, and normalization. - Strong programming skills in Python and C++. - Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform. - Familiarity with software development best practices, including version control, testing, and deployment. - Strong understanding of statistical analysis and machine learning algorithms. - Experience with data visualization tools such as Tableau or Power BI. Additional Information: - A 15 years full time education is required.