Job Description :
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.
Skills:
• PyTorch
• LangChain
• LlamaIndex
• Pinecone
• Other relevant pipeline
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.
Key Responsibilities and Duties:
- 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.
Compensation:
- Competitive salary in the range of 8 LPA to 15 LPA based on experience and qualifications.
- If you are passionate about AI and machine learning and have a proven track record in this space, we’d love to hear from you!