Roles & Responsibilities: -
Implement generative AI models, identify insights that can be used to drive business decisions.
Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.
- Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.
- Optimizing existing generative AI models for improved performance, scalability, and efficiency.
- Ensure data quality and accuracy -Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.
- Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models. -Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers
- Experience working with cloud based platforms (example: AWS, Azure or related)
- Strong problem-solving and analytical skills
- Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI
- Prior statistical modelling experience
- Demonstrable experience with deep learning algorithms and neural networks
- Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
- Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills:
- Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.
- Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.
- Must have strong knowledge of data structures, algorithms, and software engineering principles. -Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.
- Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.
- Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.
- Need to have knowledge of software development methodologies, such as Agile or Scrum.
- Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.
Additional Information:
- Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.
- strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.
- You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment.
