GEN AI Senior Consultant

We are seeking a highly experienced Senior Consultant specializing in Generative AI, with deep expertise in Large Language Models (LLMs), Python programming, and Machine Learning. The successful candidate will be tasked with designing, assessing, and implementing Generative AI solutions, effectively converting proof-of-concept (PoC) projects into robust, scalable production applications. Core Responsibilities

• Design, develop, and deploy applications leveraging Generative AI and LLM technologies.
• Create comprehensive end-to-end pipelines for LLM development and deployment, encompassing data preparation, model assessment, and performance tuning.
• Transform proof-of-concept initiatives into scalable, enterprise-grade solutions.
• Design, implement, validate, and enhance machine learning models and related applications.
• Research and adopt suitable machine learning algorithms, tools, frameworks, and data representation methods.
• Gather, cleanse, preprocess, and prepare datasets for training and evaluation, including the use of synthetic data where necessary.
• Deploy models via REST APIs and cloud-based platforms to ensure accessibility and scalability.
• Implement Responsible AI and data privacy best practices, ensuring ethical data management, transparency, bias reduction, and accountability.
• Utilize statistical analysis, data mining, and visualization techniques to support model development and inform decision-making processes.

Required Skills and Qualifications

• Proficiency in Python programming, with substantial experience in Data Science, Machine Learning, and Deep Learning methodologies.
• Hands-on expertise in Generative AI, LLM development, and prompt engineering techniques.
• Experience working with frameworks such as LangChain and Semantic Kernel.
• Knowledge of open-source and API-based Large Language Models.
• Familiarity with ML/DL frameworks including PyTorch, TensorFlow, or Keras.
• Understanding of Natural Language Processing (NLP), neural networks, computer vision, or speech processing domains.
• Experience in model evaluation, conducting experiments, building deployment pipelines, and operationalizing AI solutions in production environments.
• Awareness of Responsible AI principles, data privacy regulations, and ethical AI development practices.
• Experience with cloud-based AI and ML platforms such as Azure Machine Learning, AWS AI/ML, Google Cloud ML, or Databricks.