- Solid understanding of statistical methods, ML algorithms, and deep learning architectures.

- Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.

- 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.

- Knowledge of model interpretability and fairness frameworks (SHAP, LIME, Fairlearn) and responsible AI principles

- 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 andobjectives,



ensuring alignment with overall business goals.

- Optimizing existing generative AI models for improved performance, scalability,and efficiency.

- 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.

- Experience working with cloud based platforms (example: AWS, Azure or related)

- Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).

📌 ML Specialist (Udupi)
🏢 Niveus
📍 Udupi