AI​/ML Engineering Intern

• Competitive salary
• Dental insurance
• Health insurance
• Paid time off
• Vision insurance

We are looking for a hands-on college or university student to join Novacis Digital as an AI/ML Engineering Intern supporting the design and development of enterprise AI products using machine learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, intelligent document processing, and modern software engineering practices. The ideal candidate is a strong student engineer who can move from experimentation to working prototypes and write clean, testable Python.

• Develop and prototype AI/ML and Generative AI features using Python and modern AI frameworks.
• Build and test LLM-based applications using OpenAI, Llama, Hugging Face, or similar foundation models.
• Support RAG solutions using embeddings, vector databases, chunking, retrieval, reranking, and grounding techniques.
• Use Lang Chain, Lang Graph, or similar orchestration frameworks to build multi-step and agentic AI workflows.
• Develop lightweight APIs and services using FastAPI, Flask, or similar Python frameworks.
• Assist with model/application evaluation, prompt testing, hallucination analysis, debugging, latency analysis, and performance improvement.
• Prepare and transform structured and unstructured data for AI experimentation and product use cases.
• Support intelligent document processing, conversational analytics, workflow automation, or enterprise search prototypes.
• Use Git-based development practices and contribute technical notes, experiment results, and reusable documentation.
• Research emerging AI capabilities and convert promising approaches into demonstrable product prototypes.

• Strong programming fundamentals in Python.
• Solid understanding of Artificial Intelligence, Machine Learning, and Deep Learning fundamentals.
• Understanding of Generative AI concepts, LLMs, prompt engineering, embeddings, vectorization, and RAG.
• Hands-on academic or personal project experience with AI chatbots, AI assistants, machine learning models, or LLM-based applications.
• Exposure to Lang Chain, Lang Graph, Hugging Face, Transformers, or similar AI frameworks.
• Basic understanding of REST APIs, JSON, Git, and software development practices.
• Familiarity with SQL, pandas, Num Py, scikit-learn, PyTorch, Tensor Flow, or similar data/ML libraries.
• Strong analytical, logical, debugging, and problem-solving skills.
• Ability to communicate technical ideas clearly and work effectively in a hybrid team environment.

• Currently pursuing a B.S., M.S., or equivalent degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Science, Computer Engineering, or a related engineering discipline.
• Strong academic performance and evidence of applied engineering work are preferred.

Candidates should be able to demonstrate at least 2 hands-on AI/ML or GenAI projects involving one or more of the following:

• LLM-based applications or AI assistants
• RAG pipelines and vector database implementations
• Agentic AI workflows or tool-using agents
• Prompt engineering and structured LLM evaluation
• Machine learning models using scikit-learn, PyTorch, or Tensor Flow
• FastAPI/Flask-based AI services or application backends
• AI solutions addressing a real-world business or operational problem

• Exposure to Azure, AWS, or GCP and basic cloud deployment concepts.
• Experience with Docker, CI/CD, Linux, or containerized development environments.
• Experience with vector databases such as Pinecone, ChromaDB, FAISS, Qdrant, Milvus, or pgvector.
• Exposure to Computer Vision, NLP, intelligent document processing, conversational AI, or enterprise analytics.
• Prior…