ML Specialist

• Strong 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

Department

Data Modernization

Open Positions

1

Skills Required

Machine Learning & Deep Learning, Python (TensorFlow, PyTorch, Keras), Cloud Platforms (AWS, GCP, Azure), Natural Language Processing (SpaCy, NLTK, Hugging Face), Responsible AI & Model Interpretability (SHAP, LIME, Fairlearn)

Role

• 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).

Years Of Exp

5 to 8 years

tags

Fairlearn)