Artificial Intelligence Engineer

Vayuz Technologies is seeking an innovative and self-starting Artificial Intelligence Engineer. You will be an AI expert with a strong background in making architectural tradeoffs to optimize AI performance for a variety of use cases. This role involves close collaboration with internal and external development engineers (architecture, hardware, validation, software services), contributing to development, and supporting device characterization and benchmarking efforts.

Responsibilities

• Large Models & Deep Neural Networks: Demonstrate proficiency and hands-on experience in working with large models and deep neural networks.
• LLM Expertise: Possess expertise in LLMs with working knowledge of large language models (LLMs).
• System Architecture: Bring extensive experience in System platform Architecture.
• Development Experience: Experience in development, preferably for memory/storage/any embedded system.
• Standards & Patents: Possess in-depth knowledge and extensive experience in dealing with Standardizations, Technical Papers, and Patents.
• Programming Proficiency: Extensive experience with C/C++ and Python programming.
• LLM Development & Fine-tuning: Develop and fine-tune LLMs (e.g., GPT, Llama, Mistral, Falcon, Claude) for domain-specific applications.
• RAG Pipeline Implementation: Implement RAG (Retrieval Augmented Generation) pipelines using tools like LlamaIndex, LangGraph, and vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) to significantly enhance response accuracy.
• AI-Powered Agents: Build advanced AI-powered chatbots and autonomous agents using frameworks like LangGraph, CrewAI, and leveraging LlamaIndex and OpenAI APIs.
• Generative AI Optimization & Deployment: Optimize and deploy generative AI models for real-time inference using cloud platforms (e.g., AWS, GCP, Azure) and MLOps tools (e.g., Docker, Kubernetes, MLflow).
• Model Fine-tuning Techniques: Fine-tune models using techniques such as LoRA, QLoRA, PEFT, and RLHF to improve efficiency and personalization.
• AI-Driven Workflows: Develop AI-driven workflows for structured reasoning and decision-making using CrewAI and LangGraph.
• Multi-Modal AI Integration: Integrate multi-modal AI models (text, image, speech) into comprehensive enterprise solutions.
• Memory & Retrieval Strategies: Implement memory and retrieval strategies for LLM-based systems using vector search and caching techniques.
• Ethical AI: Ensure AI models adhere to ethical AI guidelines, incorporate bias mitigation strategies, and follow robust security best practices.

Requirements

• B.Tech in Computer Science or Electrical Engineering.
• Experience in the relevant domain.
• Strong analytical and abstract thinking ability, as well as excellent technical communication skills.
• Able to work independently and perform effectively in a fast-paced environment.
• Ability to troubleshoot and debug complex issues efficiently.
• Working knowledge of Device Drivers is desirable.
• Prior experience in working with Agile/Scrum methodologies.

Required Skills

• Languages & Frameworks: Proficiency in Python, PyTorch, TensorFlow, JAX.
• LLMs: Large Language Models (GPT, Llama, Mistral, Falcon, Claude).
• Vector Databases: FAISS, Pinecone, Weaviate, ChromaDB.
• AI Frameworks: LlamaIndex, LangGraph, CrewAI, OpenAI APIs.
• MLOps & Cloud: Docker, Kubernetes, MLflow, AWS, GCP, Azure.
• Fine-tuning: LoRA, QLoRA, PEFT, RLHF.