AI / ML Engineer

Job Description: You will be responsible for developing applications and systems that utilize AI tools, Cloud AI services, with a proper cloud or on-prem application pipeline with production-ready quality. You should be able to apply GenAI models as part of the solution, including but not limited to deep learning, neural networks, chatbots, and image processing. Key Responsibilities: - Implement generative AI models and identify insights to drive business decisions. - Collaborate with multi-functional teams to understand business problems, develop hypotheses, and test them with data. - Define AI project requirements and objectives in alignment with overall business goals. - Stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques. - Optimize existing generative AI models for improved performance, scalability, and efficiency. - Ensure data quality and accuracy. - Design and develop prompt engineering strategies to optimize the performance of GenAI models. - Implement cutting-edge NLP techniques and methodologies to enhance GenAI model capabilities. - Drive innovation and excellence in AI technology by determining effective prompt generation processes. - Work with cloud-based platforms like AWS, Azure, or related services. - Demonstrate strong problem-solving and analytical skills. - Handle various data formats and sources through Omni Channel for Speech and voice applications. - Develop clear and concise documentation to communicate complex AI concepts to technical and non-technical stakeholders. - Contribute to establishing best practices and standards for generative AI development within the organization. Qualifications Required: - Solid experience in developing and implementing generative AI models with a strong understanding of deep learning techniques. - Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, or Keras. - Strong knowledge of data structures, algorithms, and software engineering principles. - Familiarity with cloud-based platforms like AWS, GCP, or Azure. - Experience with NLP techniques and tools like SpaCy, NLTK, or Hugging Face. - Knowledge of data visualization tools and libraries like Matplotlib, Seaborn, or Plotly. - Understanding of software development methodologies such as Agile or Scrum. Company Additional Information: - A degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required, with a Ph.D. being highly desirable. - Strong communication skills are essential for effectively conveying complex technical concepts to diverse audiences. - A proactive mindset and the ability to work independently and collaboratively in a fast-paced, dynamic environment are crucial.,