Ai Ml Engineer(Gen ai)-Bengaluru/Onsite Volantis Technologies

0.0 - 1.0 years

1 - 3 Lacs

Bengaluru

Work from Office

Role & responsibilities Experience: 0-1 year Location - Bengaluru Mode of work - Work from office Mode of interview - Face to Face We are looking for a highly motivated and passionate AI/ML Engineer with a strong foundation in machine learning and hands-on project experience in Generative AI. As an early-career team member, you will work on cutting-edge technologies involving Large Language Models (LLMs), Agentic AI, and toolkits like Lang Chain, Lang Graph, and Phi Data. This role is ideal for someone who has recently completed academic or personal projects and is eager to apply their knowledge to real-world use cases. Key Responsibilities Build, experiment with, and fine-tune Generative AI models using popular LLMs (e.g., OpenAI, LLaMA, Mistral, etc.). Develop agent-based workflows using tools such as LangChain, LangGraph, and PhiData. Create interactive and dynamic AI pipelines for tasks like summarization, Q&A, sentiment analysis, and more. Collaborate with the AI/ML team to design and deploy prototypes and PoCs. Write clean, modular Python code and maintain version control via Git/GitHub. Document projects clearly and effectively for internal and external stakeholders. Required Skills Solid understanding of Machine Learning, Deep Learning fundamentals, and model evaluation. Experience with Generative AI projects (transformers, text generation, prompt engineering, etc.). Familiarity with frameworks like LangChain, LangGraph, PhiData. Proficient in Python, along with common ML libraries (e.g., PyTorch, Hugging Face Transformers, scikit-learn). Good understanding of LLM APIs (OpenAI, Anthropic, Cohere, etc.). Strong problem-solving ability and communication skills. Active GitHub profile showcasing relevant projects is mandatory Good to Have Knowledge of REST APIs, basic backend frameworks like Flask or FastAPI. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate). Basic understanding of RAG (Retrieval-Augmented Generation) pipelines. Knowledge of prompt chaining and tool-calling via LLM agents. Knowledge on web application development

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