Software Engineer Intern (AI / ML) - Spring 2027

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title as heading. Must not include Job ID etc. Must preserve all substantive info. Remove boilerplate like confidentiality, security standards, etc. Also remove application instructions (like "For jobs located in the United States, please visit the job posting..."). We need to parse the posting. Let's extract sections: - About the role: The opening paragraphs describing Snowflake's vision, AI-native thinkers, etc. Also description of role: "Software Engineer Intern (AI / ML) - Spring 2027". But we shouldn't repeat job title as heading; we can include description. - Responsibilities: Not explicitly listed; maybe "What You Will Learn/Gain" could be considered responsibilities? Actually responsibilities are tasks you will do. The posting includes "What You Will Learn/Gain" and "Possible Teams/Work Focus Areas". Those could be responsibilities or learning outcomes. We need to decide. - Requirements: Must be actively enrolled, desired class level, majors, recommended coursework, research/publications, etc. - Qualifications: Could be similar to requirements; maybe we combine. - Skills: Programming skills in Python, Golang, Java; preferred knowledge of PyTorch or CUDA; experience working as part of a team; dedication and passion. - Benefits: "What We Offer" includes paid full-time internships, exposure, chance to work with experts, opportunity to contribute, high level of access, stuff that matters: treated as member, included in meetings, flexible hours, casual dress, accommodations to work from home, swag, catered lunches, gaming consoles, recreational games, happy hours, company outings, etc. Also benefits package: medical, dental, vision, life, disability insurance; flexible spending & HSA; employee assistance program; other company benefits. - Pay: "The estimated pay range for this role is 42.00-60.00 per hour." Also mention starting hourly rate determined based on factors. - Schedule: "When: Spring 2027 Eligible start date options: January 4, 2027; January 19, 2027 Eligible end date options: March 26, 2027; April 9, 2027; May 7, 2027 Duration: 12-16 weeks recommended, more than 16 weeks also encouraged (12 month maximum)". So schedule info. We need to avoid filler like "commensurate with experience". Not present. We must not include sections with placeholder text. All sections we include must have substantive content. We must not repeat job title as heading. So we won't have

Software Engineer Intern...

. We'll just have content under About the role. We must not include Job ID/requisition numbers. We must output only HTML fragment, no /, no markdown fences. We'll produce something like:

About the role

...

Then maybe

Responsibilities

with

• ... from What You Will Learn/Gain and Possible Teams/Work Focus Areas. But we need to ensure we don't invent content. We'll extract actual sentences. Let's extract About the role content: "At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done." Then maybe also description of Snowflake's vision: "Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions. We are now a world-class organization with offices in more than a dozen countries and serving many more. Expanding on Snowflake's trust promise and with the explosion of language models, we will democratize the ability to easily glean insights from massive amounts of structured and unstructured data using AI and natural language, from running powerful batch analysis to accurately answering interactive questions about any type of data. We're looking for dedicated students who share our passion for groundbreaking technology and want to create a lasting future for Snowflake and you." That seems appropriate for About the role. Responsibilities: Could be "What You Will Learn/Gain" and "Possible Teams/Work Focus Areas". Let's list them as responsibilities (tasks you will do). The bullet points: What You Will Learn/Gain: - Engineering for Scale: Learn to build highly integrated, secure, and scalable products that enable end-to-end ML workflows - Agentic Workflows: Gain experience with agentic testing, iteration, and managing complex workflows for SQL generation - Evaluation & Trust: Understand how to build evaluation loops to measure the groundedness, reliability, and safety of AI-powered features - Multimodal Data Processing: Learn how to apply AI operations natively to both structured and unstructured data within a cloud database - High-Performance Research: Gain exposure to hardware performance optimization to achieve better LLM throughput Possible Teams/Work Focus Areas: - Applied AI: Building production-grade AI systems (agents, RAG pipelines, LLM integrations) and deploying them with strategic customers - ML Platform: Developing infrastructure for feature stores, MLOps, and highly optimized runtimes for both structured and unstructured data - LLM Products & Snowflake Intelligence: Creating AI systems that reason over governed data and shipping features like design prompts and agent workflows - AI Migrations (Agents for Code): Building intelligent agents to automate SQL code conversion and data migrations using Java, Go, and LangGraph - Cortex Search, Analyst & Agents: Developing low-latency fuzzy search (Cortex Search), natural language interfaces for business questions (Cortex Analyst), and custom AI agents - Cortex AI in SQL: Integrating generative AI directly into database queries to handle multimodal data natively We can combine these into a responsibilities section. Requirements: Must be actively enrolled in an accredited college/university program during the time of the internship; Desired class level: Masters, or PhD; Desired majors: Computer Science, Computer Engineering, Electrical Engineering, Physics, Math, or related field; Recommended coursework: artificial intelligence, machine learning, deep learning, federated learning, efficient LLMs, information retrieval, predictive & generative modeling, natural language processing, differential privacy, cloud computing, distributed & operating systems; Research or publications in AI, ML, NLP, or CV or major contributions to open source. Qualifications: Could be similar; maybe we treat "Excellent programming skills in Python, Golang, and Java; Preferred knowledge of PyTorch or CUDA; Experience with working as a part of a team; Dedication and passion for technology" as Qualifications or Skills. Let's separate: Qualifications could be education and experience; Skills could be technical skills. But we need to avoid duplication. Let's decide: - Requirements: enrollment, class level, majors, coursework, research/publications. - Qualifications: maybe not needed separately; we could combine with Requirements. But we need to follow instruction: use headings only when posting has real specific content. If we think Qualifications overlaps with Requirements, we could omit Qualifications section. However we have distinct content: "Excellent programming skills in Python, Golang, and Java; Preferred knowledge of PyTorch or CUDA; Experience with working as a part of a team; Dedication and passion for technology". That could be Skills. Thus we can have: - Requirements (education, enrollment, coursework, research) - Skills (programming languages, PyTorch/CUDA, teamwork, dedication) - Benefits (What We Offer + benefits package) - Pay (pay range) - Schedule (when, start/end dates, duration) We also need About the role. Responsibilities we already have. Thus sections: About the role, Responsibilities, Requirements, Skills, Benefits, Pay, Schedule. We must not include Qualifications if we don't have distinct content; we can omit. Now we need to format. Use

  for each section heading. Use

  • for any list of duties/requirements/benefits. Use

    for prose. We must preserve ALL substantive information; do not invent or summarize away detail. We need to ensure we include all details from the posting, except boilerplate. Let's extract each piece precisely. About the role: We'll combine the two paragraphs about Snowflake vision and AI-native thinkers. Ensure we keep all sentences. Let's copy: "At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions. We are now a world-class organization with offices in more than a dozen countries and serving many more. Expanding on Snowflake's trust promise and with the explosion of language models, we will democratize the ability to easily glean insights from massive amounts of structured and unstructured data using AI and natural language, from running powerful batch analysis to accurately answering interactive questions about any type of data. We're looking for dedicated students who share our passion for groundbreaking technology and want to create a lasting future for Snowflake and you." That seems complete. Responsibilities: We'll list bullet points from What You Will Learn/Gain and Possible Teams/Work Focus Areas. We need to ensure we don't lose any detail. What You Will Learn/Gain bullet points: - Engineering for Scale: Learn to build highly integrated, secure, and scalable products that enable end-to-end ML workflows - Agentic Workflows: Gain experience with agentic testing, iteration, and managing complex workflows for SQL generation - Evaluation & Trust: Understand how to build evaluation loops to measure the groundedness, reliability, and safety of AI-powered features - Multimodal Data Processing: Learn how to apply AI operations natively to both structured and unstructured data within a cloud database - High-Performance Research: Gain exposure to hardware performance optimization to achieve better LLM throughput Possible Teams/Work Focus Areas bullet points: - Applied AI: Building production-grade AI systems (agents, RAG pipelines, LLM integrations) and deploying them with strategic customers - ML Platform: Developing infrastructure for feature stores, MLOps, and highly optimized runtimes for both structured and unstructured data - LLM Products & Snowflake Intelligence: Creating AI systems that reason over governed data and shipping features like design prompts and agent workflows - AI Migrations (Agents for Code): Building intelligent agents to