We are seeking an experienced AI/ML Lead Engineer with expertise in generative AI and Retrieval- Augmented Generation (RAG) systems. The ideal candidate should have in-depth knowledge of GPT- 3.5 Turbo, GPT-4, and other advanced Large Language Models (LLMs). You will be responsible for developing and maintaining machine learning pipelines, leveraging cutting-edge AI technologies to solve complex real-world problems.
Responsibilities:
Utilize advanced LLMs such as GPT-3.5 Turbo, GPT-4, and Open LLM frameworks to build AI models for various applications.
Data Collection Preprocessing: Collect, preprocess, and analyze large volumes of structured and unstructured data from diverse sources.
ML Pipeline Development: Design and maintain scalable machine learning pipelines for training, evaluation, and deployment of AI models.
Proficiency in LangChain and LLMs: Perform tasks such as summarization, classification, Named Entity Recognition (NER), and question answering using LangChain and other Open LLM frameworks.
Generative AI Techniques: Work with prompt engineering, vector databases, and LLMs like OpenAI, LlamaIndex, Azure OpenAI, and open-source LLMs to deliver solutions.
GenAI RAG Expertise: Apply Generative AI technologies, including RAG architecture, fine- tuning techniques, and inferencing frameworks.
Continuous Learning: Stay updated on the latest advancements in AI and ML and integrate them into the projects to improve outcomes.
Model Testing Validation: Conduct thorough testing and validation of machine learning models to ensure their reliability, scalability, and robustness.
Documentation Collaboration: Document code, algorithms, and workflows to facilitate team collaboration and knowledge sharing.
Conduct thorough testing and validation of machine learning models to ensure reliability, robustness, and scalability.
Document code, algorithms, and processes to facilitate knowledge sharing and collaboration within the team.
Participate in brainstorming sessions and contribute innovative ideas to enhance the performance and functionality of AI/ML applications.
Support data preprocessing, feature engineering, and data visualization tasks to prepare datasets for model training and evaluation.
Learn and apply best practices in AI/ML development, including model selection, hyperparameter tuning, and model evaluation techniques.
Qualifications:
6+ years of experience in AI/ML, with a strong focus on generative AI, LLMs, and RAG systems. Proficiency in Python and its libraries for machine learning and data analysis (e.g., PyTorch). Hands-on experience with LangChain, Pinecone, LlamaIndex, and OpenAI models. Proven track record of building scalable machine learning systems and pipelines. Strong understanding of generative techniques, RAG architecture, and prompt engineering. Familiarity with both cloud-based and open-source LLM frameworks such as Azure OpenAI and LlamaIndex.
Skills
Competitive salary in the range of 8 LPA to 15 LPA based on experience and qualifications.
Opportunity to work on diverse AI/ML projects spanning various industries and domains.