Ai engineer intern

1 week ago

Anand, India Signet Arms Full time

Company: Signet Arms Location: Remote (India) Type: Paid Internship (Full Time) Duration: 3–6 months (with potential extension) Company Description Signet Arms is an innovative defense technology company. We are building next-generation agentic AI systems, enabling autonomous reasoning, workflow orchestration, and intelligent automation. Our work combines LLM engineering, applied ML, and modern AI toolchains to push the boundaries of engineering automation.  Role Description We are seeking a highly motivated AI Engineering Intern to support the development, fine-tuning, and deployment of LLM-based agentic systems. You will work closely with our engineering team to prototype, evaluate, and optimize AI agents that integrate with complex technical workflows. Responsibilities • Work with state-of-the-art LLMs (Open AI, Anthropic, etc.) for evaluation, tuning, and optimization. • Fine-tune LLMs on domain-specific datasets. • Build components of agentic AI systems, including planning, tool-use, and multi-step reasoning. • Develop RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector stores, and structured retrieval. • Use Lang Graph (or similar frameworks) to design and implement agent workflows. • Contribute to ML experiments using deep learning frameworks such as Py Torch or Tensor Flow. • Work on cloud platforms (AWS or Oracle Cloud) for model deployment, storage, and scalable compute. • Perform benchmarking, error analysis, and iterative improvement of AI systems. Qualifications Must-Have Skills • Strong foundation in machine learning and deep learning. • Hands-on experience with LLMs (APIs, fine-tuning, or system integration). • Understanding of RAG architectures, embeddings, and vector databases. • Familiarity with Lang Graph, Lang Chain, or similar agent frameworks. • Solid Python programming skills and ability to write clean, modular code. • Basic knowledge of cloud platforms (AWS or Oracle Cloud). Nice-to-Have • Experience with MLOps concepts or distributed compute. • Knowledge of data engineering or pipeline orchestration. • Research or project experience involving LLM evaluation or agent architectures.

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