Software Engineer Intern (AI / ML) - Spring 2027
Snowflake · Menlo Park, CA · 3 wk ago
EngineeringFull-time
We need to output HTML fragment with sections: h3 headings for sections present. Must not repeat job title. Must not include Job ID etc. Must include only sections with real content. Must not include boilerplate like confidentiality, etc. Must remove cookie/navigation/legal/EEO etc. Must preserve all substantive info.
We need to parse the posting.
Key sections:
- About the role? The intro paragraphs describing Snowflake and role. Could be "About the role" or maybe "About Snowflake". The instruction: use h3 for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to decide which headings apply.
We have content: description of Snowflake, mission, what they seek. Could be "About the role" or "About Snowflake". Probably "About the role". Then "What We Offer" corresponds to Benefits. "What We Expect" corresponds to Requirements/Qualifications/Skills. "What You Will Learn/Gain" maybe "Learning Opportunities" but not in list; could be under "Responsibilities"? Actually it's what you will learn, could be a section like "Learning & Development". Not in prescribed headings but we can still use h3 for any section heading? The instruction says use h3 for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It implies we should use those standard headings when applicable, but we can also create other headings if needed? It says "Use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but suggests using those. Probably we should map content to those headings.
We have:
- About the role: introductory paragraphs about Snowflake and the intern role.
- Responsibilities: maybe not explicitly listed; but we have "What You Will Learn/Gain" and "Possible Teams/Work Focus Areas". Could be responsibilities.
- Requirements: "What We Expect" includes eligibility, majors, coursework, skills.
- Qualifications: similar to requirements; maybe combine.
- Skills: programming skills, PyTorch/CUDA, teamwork.
- Benefits: "What We Offer" includes paid internship, culture, etc. Also later compensation and benefits package.
- Pay: compensation range given.
- Schedule: start/end dates, duration.
We must not include sections with placeholder or vague like "commensurate with experience". We have actual pay range and schedule.
We must not include boilerplate like confidentiality, security standards, etc. Remove those lines.
Also remove application instructions like "For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com". Also remove the line about notifying if non-compliant.
We must preserve all substantive information.
Let's extract substantive content:
Intro:
"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 job title line: "Software Engineer Intern (AI / ML) - Spring 2027" (but we must not repeat as heading). We can keep it maybe as a paragraph? The instruction: do NOT repeat the job title as a heading (the page already shows it). It doesn't say we cannot include it elsewhere; but we could keep it as a paragraph? Probably better to omit it entirely because it's not substantive beyond title. But we might keep it as a line? Safer to omit.
Then description of Snowflake history: "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's part of About the role.
Then "What We Offer:" bullet list (actually sentences). Let's extract:
- Paid, full-time internships in the heart of the software industry
- Exposure to a fast-paced, fun, and inclusive culture
- A chance to work with world-class experts on challenging projects
- Opportunity to provide meaningful contributions to a real system used by customers
- High level of access to supervisors (manager and mentor), detailed direction without micromanagement, feedback throughout your internship, and a final evaluation
- Stuff that matters: treated as a member of the Snowflake team, included in company meetings/activities, flexible hours, casual dress code, accommodations to work from home, swag, and much more
- Catered lunches, access to gaming consoles, recreational games, happy hours, company outings, and more
Then later compensation and benefits: "The following represents the expected range of compensation for this role: The estimated pay range for this role is 42.00-60.00 per hour. The successful candidate’s starting hourly rate will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; flexible spending & health savings account; employee assistance program; and other company benefits."
We should include Pay section with the range, and Benefits section with the list of benefits (including those from What We Offer and the benefits package). However we must not duplicate. We can combine.
What We Expect:
- 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
- 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)
- 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
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 also have confidentiality etc lines to remove.
Now we need to decide sections.
Potential sections:
- About the role (intro + Snowflake description)
- Responsibilities (maybe combine What You Will Learn/Gain and Possible Teams/Work Focus Areas? Actually responsibilities are what you'll do; learning outcomes are not responsibilities. Could treat "What You Will Learn/Gain" as responsibilities? Might be better to have a section "Learning Opportunities" but not in list. Could use "Responsibilities" for the teams/work focus areas (what you might work on). And "What You Will Learn/Gain" could be under "Responsibilities" as well? Or we could make a section "What You'll Learn" but not in prescribed headings. The instruction says prefer a few substantive sections over many thin ones. So we could combine learning and teams into Responsibilities.
- Requirements/Qualifications/Skills: Could combine into one "Requirements" section covering eligibility, class level, majors, coursework, research, programming skills, preferred knowledge, team experience, dedication.
- Benefits: combine What We Offer and benefits package (medical etc). Also maybe include flexible hours etc.
- Pay: hourly range.
- Schedule: start/end dates, duration.
We must not include sections with placeholder text. All have real content.
We must not include the confidentiality lines.
Now produce HTML fragment.
We'll use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but suggests using those. Probably we should map content to those headings.
We have:
- About the role: introductory paragraphs about Snowflake and the intern role.
- Responsibilities: maybe not explicitly listed; but we have "What You Will Learn/Gain" and "Possible Teams/Work Focus Areas". Could be responsibilities.
- Requirements: "What We Expect" includes eligibility, majors, coursework, skills.
- Qualifications: similar to requirements; maybe combine.
- Skills: programming skills, PyTorch/CUDA, teamwork.
- Benefits: "What We Offer" includes paid internship, culture, etc. Also later compensation and benefits package.
- Pay: compensation range given.
- Schedule: start/end dates, duration.
We must not include sections with placeholder or vague like "commensurate with experience". We have actual pay range and schedule.
We must not include boilerplate like confidentiality, security standards, etc. Remove those lines.
Also remove application instructions like "For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com". Also remove the line about notifying if non-compliant.
We must preserve all substantive information.
Let's extract substantive content:
Intro:
"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 job title line: "Software Engineer Intern (AI / ML) - Spring 2027" (but we must not repeat as heading). We can keep it maybe as a paragraph? The instruction: do NOT repeat the job title as a heading (the page already shows it). It doesn't say we cannot include it elsewhere; but we could keep it as a paragraph? Probably better to omit it entirely because it's not substantive beyond title. But we might keep it as a line? Safer to omit.
Then description of Snowflake history: "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's part of About the role.
Then "What We Offer:" bullet list (actually sentences). Let's extract:
- Paid, full-time internships in the heart of the software industry
- Exposure to a fast-paced, fun, and inclusive culture
- A chance to work with world-class experts on challenging projects
- Opportunity to provide meaningful contributions to a real system used by customers
- High level of access to supervisors (manager and mentor), detailed direction without micromanagement, feedback throughout your internship, and a final evaluation
- Stuff that matters: treated as a member of the Snowflake team, included in company meetings/activities, flexible hours, casual dress code, accommodations to work from home, swag, and much more
- Catered lunches, access to gaming consoles, recreational games, happy hours, company outings, and more
Then later compensation and benefits: "The following represents the expected range of compensation for this role: The estimated pay range for this role is 42.00-60.00 per hour. The successful candidate’s starting hourly rate will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; flexible spending & health savings account; employee assistance program; and other company benefits."
We should include Pay section with the range, and Benefits section with the list of benefits (including those from What We Offer and the benefits package). However we must not duplicate. We can combine.
What We Expect:
- 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
- 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)
- 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
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 also have confidentiality etc lines to remove.
Now we need to decide sections.
Potential sections:
- About the role (intro + Snowflake description)
- Responsibilities (maybe combine What You Will Learn/Gain and Possible Teams/Work Focus Areas? Actually responsibilities are what you'll do; learning outcomes are not responsibilities. Could treat "What You Will Learn/Gain" as responsibilities? Might be better to have a section "Learning Opportunities" but not in list. Could use "Responsibilities" for the teams/work focus areas (what you might work on). And "What You Will Learn/Gain" could be under "Responsibilities" as well? Or we could make a section "What You'll Learn" but not in prescribed headings. The instruction says prefer a few substantive sections over many thin ones. So we could combine learning and teams into Responsibilities.
- Requirements/Qualifications/Skills: Could combine into one "Requirements" section covering eligibility, class level, majors, coursework, research, programming skills, preferred knowledge, team experience, dedication.
- Benefits: combine What We Offer and benefits package (medical etc). Also maybe include flexible hours etc.
- Pay: hourly range.
- Schedule: start/end dates, duration.
We must not include sections with placeholder text. All have real content.
We must not include the confidentiality lines.
Now produce HTML fragment.
We'll use for each section heading.
Inside sections, use
for prose,
- for lists.
We need to ensure we don't include any markdown.
Let's craft.
Section About the role:
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