Responsibilities:

• Design and implementscalablegenerativeAI and machine learning solutionsfor business problems.

• Develop, train, and fine-tuneML and deep learning models using frameworks such asPyTorch,Keras,TensorFlowor Scikit-learn.

• Collaboratewith data engineers and software developers to integrate AI models into production systemsthrough APIs, vector databases, and orchestration frameworks (e.g.,LangChain,LlamaIndex).

• Experiment with and evaluategenerative AI techniques such as retrieval-augmented generation (RAG), reinforcement learning from human feedback (RLHF), and model distillation.

• Analyze large datasetsto extract meaningful insights and features for model training.

• Evaluate model performanceusing statistical methods, experiment tracking, A/Btestingand LLM evaluation techniques. 

• Ensure compliancewith responsible AI standards — including fairness, transparency, and data governance.

• Stay updatedwith advancements in AI & ML to propose innovative solutions.

Education and Qualifications/Skills:

• Bachelor's orMaster's degree in Computer Science/Engineeringor related field.

• 3-7 years of experience.

• Good understanding of the foundations and working principles of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory.

• Knowledge of at least one of the following domains: generative AI, statistical learning, optimization, NLP, deeplearningor time series analysis.