{"id":3418987,"url":"https://alion.io/job/nexgen-tech-ai-engineer-intern","title":"AI Engineer Intern","company":{"id":1220925,"name":"Nexgen Tech","domain":"nexgentech.ca","url":"https://alion.io/company/nexgentech","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Embeddings","optional":false},{"name":"Git","optional":false},{"name":"Hugging Face","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"OpenAI","optional":false},{"name":"Pandas","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"FAISS","optional":true},{"name":"FastAPI","optional":true},{"name":"Flask","optional":true},{"name":"GCP","optional":true},{"name":"GitHub","optional":true},{"name":"Hallucination","optional":true},{"name":"Pinecone","optional":true},{"name":"Streamlit","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-10-28T17:18:00Z","employer_posted_date":null,"last_verified_at":"2026-10-28T17:18:00Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"About NexGen Tech Solutions\nNexGen Tech Solutions is a global IT services, AI engineering, and digital transformation company headquartered in Frisco, Texas, USA, with delivery operations across India and international markets.\nThe company specializes in Artificial Intelligence, Generative AI, Agentic AI, Cloud Computing, Data Engineering, Cybersecurity, and Enterprise Software Development.\nThrough its AI-focused platforms and engineering expertise, NexGen helps organizations design, develop, and deploy intelligent, scalable, and secure technology solutions across multiple industries.\nAt NexGen, we are committed to innovation, continuous learning, and developing next-generation AI-powered solutions that solve real-world business challenges.\n\nJob Summary\nWe are seeking a highly motivated and enthusiastic AI Engineer Intern to join our technology team. The ideal candidate should have a strong foundation in Python programming, Machine Learning (ML), Deep Learning, and Generative AI technologies.\nAs an AI Engineer Intern, you will work closely with experienced engineers and data scientists to develop, test, and optimize AI-powered applications, including Large Language Models (LLMs), intelligent automation solutions, and data-driven systems.\nThis internship provides hands-on exposure to real-world AI projects, modern AI frameworks, and emerging technologies.\nKey Responsibilities\nAssist in designing, developing, and implementing AI/ML models and applications.\nWork with Large Language Models (LLMs) and Generative AI technologies to build intelligent solutions.\nDevelop and test AI-powered applications using Python and relevant frameworks.\nSupport the development of Retrieval-Augmented Generation (RAG) pipelines, AI chatbots, and conversational AI systems.\nExplore prompt engineering techniques to improve LLM accuracy and performance.\nAssist in integrating AI models with applications through REST APIs.\nPerform data preprocessing, cleaning, transformation, and exploratory data analysis.\nExperiment with open-source AI models and APIs, including OpenAI, Hugging Face, and other LLM platforms.\nSupport model evaluation, testing, debugging, and performance optimization.\nCollaborate with software engineers, data scientists, and product teams on AI-driven projects.\nDocument technical workflows, experiments, and project outcomes.\nStay updated with emerging trends and advancements in Artificial Intelligence and Generative AI.\nRequired Technical Skills\nProgramming & Development\nGood understanding of Python programming.\nFamiliarity with libraries such as NumPy, Pandas, and Scikit-learn.\nBasic understanding of REST APIs, Git, and software development practices.\nArtificial Intelligence & Machine Learning\nFundamental knowledge of Machine Learning algorithms and concepts.\nUnderstanding of supervised and unsupervised learning.\nBasic knowledge of Deep Learning and Neural Networks.\nFamiliarity with TensorFlow or PyTorch.\nGenerative AI & LLMs\nBasic understanding of Generative AI and Large Language Models.\nFamiliarity with prompt engineering concepts.\nAwareness of LLM frameworks such as LangChain or LlamaIndex.\nBasic understanding of embeddings, vector databases, and RAG architecture.\nData & Databases\nBasic SQL knowledge.\nUnderstanding of data preprocessing and data analysis.\nFamiliarity with JSON and structured/unstructured datasets.\nGood to Have Skills\nExperience with OpenAI APIs, Hugging Face Transformers, or open-source LLMs.\nExposure to vector databases such as FAISS, ChromaDB, or Pinecone.\nUnderstanding of AI agents and agentic workflows.\nFamiliarity with FastAPI, Flask, or Streamlit.\nBasic knowledge of cloud platforms such as AWS, Azure, or Google Cloud.\nUnderstanding of Docker and AI model deployment.\nExperience with academic projects, personal AI applications, or GitHub contributions.\nFamiliarity with model evaluation, hallucination mitigation, and responsible AI practices.\nQualifications\nCurrently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical discipline.\nStrong analytical and problem-solving abilities.\nGood understanding of programming fundamentals and data structures.\nAbility to learn new technologies quickly.\nStrong communication skills and willingness to collaborate in a team environment.\nPassion for Artificial Intelligence, Generative AI, and emerging technologies.\nWhat You Will Gain\nPractical experience developing real-world AI and Generative AI applications.\nHands-on exposure to LLMs, RAG, prompt engineering, and modern AI frameworks.\nOpportunity to work alongside experienced AI engineers and technology professionals.\nExperience with AI model integration, testing, evaluation, and deployment.\nExposure to industry-standard 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