GenAI Engineer

JD:

1. Data extraction, retrieval & summarization using LLMs
2. Knowledge about graph
3. Integrating RAG and implementing efficient vectorization.
4. Optimizes LLM API calls for specific querying tasks.
5. Knows LLM API optimization techniques like time to first token, time between token, retry, error handling etc.
6. Knows about prompt engineering
7. Hands-on exp on fast api with python
8. Knowledge on react framework and how PWA works
9. Fine tuning LLM calls, nice to have

• Minimum 5 years of experience in machine learning engineering and AI development
  • Deep expertise in machine learning algorithms and techniques like supervised/unsupervised learning, deep learning, reinforcement learning, etc.
  • Solid experience in natural language processing (NLP) - language models, text generation, sentiment analysis, etc.
  • Proven understanding of generative AI concepts like text/image/audio synthesis, diffusion models, transformers, etc.
  • Hands-on experience developing and deploying generative AI applications (text generation, conversational AI, image synthesis, etc.)
  • Experience in MLOps and ML model deployment pipelines.
  • Proficiency in programming languages like Python, and ML frameworks like TensorFlow, PyTorch, etc.
  • Knowledge of cloud platforms (AWS, GCP, Azure) and tools for scalable ML solution deployment
  • Experience with data processing, feature engineering, and model training on large datasets.
  • Familiarity with responsible AI practices, AI ethics, model governance and risk mitigation
  • Understanding of software engineering best practices and applying them to ML systems.
  • Experience with an agile development environment.
  • Exposure in tools/framework to monitor and analyse ML model performance and data accuracy.
  • Strong problem-solving, analytical, and communication abilities
  • Bachelors or master’s degree in computer science, AI, Statistics, Math or related fields