AI/ML Intern

3 weeks ago

Vellore, India Steps AI Full time

Job Description:

Job Title: AI/ML Intern

Location: Remote

Duration: 6 months+ (Starting immediately)

Job Type: Paid, Full-Time Internship


About us:

Steps AI is a cutting-edge AI company focused on delivering innovative AI-powered products that revolutionize enterprise data retrieval and automation. As we expand our offerings in AI product development and consultation, we are seeking a highly skilled and motivated Machine Learning Intern. This role will place you at the forefront of cutting-edge AI technologies, including Large Language Models (LLMs), multi-agent systems, LLMOps, Local LLM deployment/orchestration, and Generative AI (GenAI) strategies.


You will be an integral part of a dynamic team, contributing to advanced machine learning (ML), deep learning (DL), and natural language processing (NLP) projects. Our ideal candidate will have a deep understanding of transformer architectures, strong foundation of LLM techniques and models, strong MLOps foundations, and experience in deploying AI solutions in real-world applications. You will also be responsible for implementing LLM orchestration techniques and multi-agent systems, where multiple LLM-based agents collaborate on complex tasks. This position will offer you the opportunity to gain hands-on experience with cutting-edge LLM Ops, MLOps, and advanced prompting strategies like Chain of Thought (CoT) and Graph of Thought (GoT) to optimize LLM performance for enterprise use cases.


Key Responsibilities:


  • LLM Development: Build and fine-tune LLMs and multi-agent systems for enterprise use cases.
  • LLM Ops: Deploy scalable MLOps pipelines and optimize LLM performance in production.
  • Transformer Models: Work with advanced models (LLama, GPT, etc.), optimizing for cloud deployment.
  • RAG Pipelines: Design and implement efficient RAG systems (Graph, Struct, Naive) for enhanced retrieval.
  • Prompt Engineering: Refine prompts using techniques like CoT, ToT, and GoT to improve LLM accuracy.
  • Multi-Agent Systems: Develop LLM-based agents for dynamic tasks using orchestration frameworks.
  • Research: Prototype advanced LLM orchestration and RAG pipelines for fast deployment.


Technical Skills Expectations:


  • We don’t expect the candidates to have production ready hand-on experience in the latest LLM technologies (we will figure that together), but, we will critically evaluate your problem statement understanding, system design, theoretical understanding of LLM techniques/models, hands-on coding experience in these domains, also, the application should take ownership in the tasks assigned to them.
  • Strong understanding of Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) with hands-on experience in Large Language Models (LLMs).
  • In-depth knowledge of transformer architectures, including BERT, GPT, T5, and state-of-the-art models such as GPT-4, Mistral, or LLaMA.
  • Proficiency in building and deploying RAG pipelines, with practical knowledge of Graph RAG, StructRAG, and Naive RAG methodologies.
  • Must have the ability to design, deploy, and maintain production-level RAG pipelines with optimized retrieval, ranking, and generative model interactions.
  • Pseudo-code comprehension and understanding of RAG systems will be evaluated during the interview process.
  • Experience in designing, deploying, and orchestrating multi-agent systems using LLM-based agents for dynamic task execution across various tools and platforms using langgraph, langchain, autogen, or llamaindex.
  • Familiarity with tool-calling frameworks, LLM-sandboxing, and how LLMs can interact with external systems (e.g., databases, APIs).
  • Strong foundation in MLOps practices for deploying scalable, production-ready AI models, with experience in Docker, Kubernetes, AWS, or Azure.
  • Experience with advanced prompting techniques, including Chain of Thought (CoT), Tree of Thought (ToT), Graph of Thought (GoT), to improve model reasoning and decision-making capabilities.
  • Proficiency with frameworks like PyTorch, TensorFlow, JAX, and frameworks like LangChain, Hugging Face, transformers, llamaindex, ollama, LLM360, texgen-webUI, or other model orchestration libraries
  • Excellent communication skills and the ability to work collaboratively with other AI engineers, DevOps professionals, and full-stack developers.
  • Ability to translate complex ML and AI concepts into actionable product features and deliverables for enterprise clients.


Educational Qualifications:


  • Pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field (preferred)
  • Strong academic background in Machine Learning, AI, or NLP. Research publications in these fields will be a plus.


What We Offer:


  • Be one of the first to get hands-on experience on latest technologies, an opportunity to work with cutting-edge LLM and GenAI technologies, multi-agent systems, and real-world enterprise AI products.
  • Mentorship from experienced AI engineers and exposure to the latest tools, techniques, and research in AI.
  • A flexible and dynamic work environment with potential for future full-time positions based on performance.

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