AI Developer

3 - 7 years

0 Lacs

Posted:17 hours ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Role Overview: You should have a good understanding of various Generative AI techniques including GANs, VAEs, and other relevant architectures. Your experience in applying these techniques to real-world problems for tasks such as image and text generation will be crucial. Make sure you are conversant with Gen AI development tools like Prompt engineering, Langchain, Semantic Kernels, and Function calling. Exposure to both API-based and open-source LLMs based solution design is expected. Key Responsibilities: - Get to the heart of customer issues, diagnose problem areas, design innovative solutions, and facilitate deployment resulting in client delight as part of the Infosys consulting team. - Develop a proposal by owning parts of the proposal document and giving inputs in solution design based on areas of expertise. - Plan the activities of configuration, configure the product as per the design, conduct conference room pilots, and assist in resolving any queries related to requirements and solution design. - Conduct solution product demonstrations, POC, Proof of Technology workshops, and prepare effort estimates which suit the customer budgetary requirements and are in line with the organization's financial guidelines. - Actively lead small projects and contribute to unit-level and organizational initiatives with the objective of providing high-quality, value-adding solutions to customers. Qualification Required: - An overall understanding of machine learning algorithms including linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks. - Proficiency in data science tools such as NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras. - Familiarity with cloud computing platforms like AWS, Azure, GCP. - Knowledge of natural language processing, NLP Transformer models, attention mechanisms, word embeddings. - Experience in computer vision, convolutional neural networks, recurrent neural networks, object detection. - Exposure to robotics, reinforcement learning, motion planning, control systems. - Understanding of data ethics, bias in machine learning, fairness in algorithms.,

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