Executive - Technology

About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focussed and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

Responsibilities

Key Responsibilities:

• Design, develop, and deploy machine learning and deep learning models for a variety of business problems.
• Work with NLP techniques such as text classification, information extraction, sentiment analysis, and language modeling.
• Collaborate with cross-functional teams to understand requirements and deliver AI-driven solutions.
• Stay up-to-date with the latest advancements in AI/ML and GenAI.
• Implement proof-of-concepts and participate in client presentations as required.
  

Required Skills And Qualifications

• Bachelor's/Master's degree in Computer Science, Engineering, Mathematics, or related field.
• Strong understanding of fundamental AI/ML algorithms and techniques.
• Hands-on experience with Machine Learning frameworks (e.g., scikit-learn, XGBoost, LightGBM) and Deep Learning libraries (e.g., TensorFlow, PyTorch, Keras).
• Experience working on NLP tasks such as text preprocessing, named entity recognition, text summarization, etc.
• Familiarity with the basics of Generative AI (LLMs, diffusion models, prompt engineering).
• Proficient in Python and relevant data science tools.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
  

Qualifications

• Experience in building and deploying AI/ML models in production environments.
• Knowledge of cloud platforms (e.g., AWS, Azure, GCP).
• Experience with MLOps tools and practices.
• Publications or participation in AI/ML competitions.