Machine Learning Development Intern Description - Description: The main objective of this internship program is to train and develop students to contribute to cutting-edge projects in Machine Learning (ML), and Generative AI (GenAI). Interns will take responsibility for key aspects of ongoing projects, gaining hands-on experience in ML model development and deployment. They will be involved in training, collaborative work, and practical tasks aimed at enhancing their skills in a corporate environment focused on innovation in AI. Role: - Support the development of ML models, with a focus on Generative AI and Prompt Engineering; - Assist the ML team in fine-tuning models, optimizing prompt inputs, and improving output quality for AI-driven applications; - Collaborate with engineers and data scientists to understand project requirements and provide solutions for building and deploying AI-based chatbots and applications; - Participate in technical meetings and brainstorming sessions to improve model performance; - Research the latest trends and breakthroughs in GenAI and contribute to experimentation with new techniques; - Help document the development process, maintaining quality standards and best practices in model iteration and deployment. - Qualifications: - Students in Computer Science / Data Science / Machine Learning / Artificial Intelligence / Engineering or related fields from the 2nd semester onwards; - Knowledge of machine learning algorithms, deep learning, natural language processing (NLP), and AI model architectures; - Strong interest in Generative AI, chatbot development, and prompt engineering; - Basic experience with Python, TensorFlow, PyTorch, or other ML frameworks; - Curiosity about cloud computing, large language models (LLMs), and AI-driven solutions; - Strong analytical and problem-solving skills with a passion for AI research and development; - Intermediate proficiency in English is required. #LI-POST Job - Administration Schedule - Part time Shift - No shift premium (Brazil) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal"
Summary
Interns contribute to ML model development and deployment focused on Generative AI and prompt engineering, fine-tuning models and building AI chatbots with engineers and data scientists. Requires enrollment in CS/Data Science/AI/Engineering from the 2nd semester, ML and NLP knowledge, basic Python/TensorFlow/PyTorch experience, and intermediate English.
Responsibilities
Support ML model development focused on GenAI and prompt engineering; assist fine-tuning models and optimizing prompts; collaborate with engineers and data scientists on AI chatbots; participate in technical meetings; research GenAI trends; document development process.
Qualifications
Students in CS/Data Science/ML/AI/Engineering from 2nd semester; knowledge of ML algorithms, deep learning, NLP, AI architectures; interest in GenAI, chatbots, prompt engineering; basic Python/TensorFlow/PyTorch; curiosity about cloud computing, LLMs; analytical and problem-solving skills; intermediate English.
Education requirements
Students in Computer Science / Data Science / Machine Learning / Artificial Intelligence / Engineering or related fields from the 2nd semester onwards.
Experience requirements
Basic experience with Python, TensorFlow, PyTorch, or other ML frameworks.