Snowflake

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.<h2>Build Core Data Engineering Primitives at Cloud Scale</h2>Data pipelines are foundational infrastructure — when they're fast, correct, and maintainable, customers build on them with confidence. If you've spent the bulk of your career building large-scale data infrastructure — designing streaming or transformation primitives, reasoning hard about consistency and fault tolerance, and owning the systems that run under millions of customer workloads — this role might be for you. You'll be working on the streaming and transformation layer at Snowflake: the constructs that define how customers move, shape, and maintain data. AI has a real presence in this work — in how customers use these pipelines and in how we think about building them — but the core job is hard distributed systems engineering, and that's what we're hiring for.<h2>About the Team</h2>We build the core data engineering primitives that power Snowflake's streaming and transformation capabilities. From the constructs customers use to define real-time pipelines to the execution fabric that makes those pipelines reliable and cost-efficient at cloud scale, our team owns the full stack of declarative data engineering. We're a small, high-ownership team operating close to the product — which means your decisions ship, your architecture matters, and your fingerprints are on some of the most-used features in Snowflake's data engineering portfolio.<h2>What You'll Do</h2><ul><li>Define and drive the technical direction for Snowflake's core data engineering and streaming transformation primitives, spanning Streams, Tasks, Dynamic Tables, and adjacent pipeline constructs.</li><li>Identify and lead multi-quarter technical investments — performance, scalability, correctness, and reliability — translating ambiguous problem spaces into concrete engineering plans with measurable outcomes.</li><li>Partner with product, research, and peer engineering teams to co-design primitives that compose cleanly across the data engineering stack.</li><li>Operate as a force multiplier: run architectural reviews, set the technical bar for design documents, and help engineers grow through high-quality feedback and sponsorship.</li><li>Work directly with customers and field teams to understand real-world usage patterns; use that signal to prioritize what matters next.</li><li>Contribute to Snowflake's technical reputation — through internal design influence, external talks, or research publications in the data engineering space.</li></ul><h2>What We're Looking For</h2><ul><li>15+ years of experience designing, building, and operating large-scale distributed data systems.</li><li>Deep expertise in at least one core area: stream processing, declarative query execution, pipeline orchestration, or data transformation at scale.</li><li>Strong computer science fundamentals — distributed systems, algorithms, fault tolerance, and consistency models.</li><li>Proficiency in C++ or Java; comfort with systems-level reasoning (latency, throughput, resource efficiency at cloud scale).</li><li>Demonstrated ability to lead cross-team technical initiatives from blank-page architecture through production at petabyte scale across thousands of concurrent workloads.</li><li>Strong written and verbal communication skills; ability to represent complex technical trade-offs clearly to engineering, product, and leadership audiences.</li></ul><h2>Nice to Have</h2><ul><li>Experience with a major analytical DBMS (Snowflake, BigQuery, Redshift, Databricks, Teradata).</li><li>Hands-on background in streaming or event-driven systems (Flink, Kafka, Spark Structured Streaming).</li><li>Familiarity with the broader data engineering ecosystem: dbt, Airflow, Fivetran, Iceberg, Delta Lake.</li><li>Experience with CDC, change propagation, or incremental computation patterns.</li><li>Advanced degree (MS or PhD) in Computer Science, with emphasis on database or distributed systems.</li></ul>Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.How do you want to make your impact?For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: <a target="_blank" rel="noopener noreferrer ugc" href="http://careers.snowflake.com">careers.snowflake.com</a>

Prinicpal Software Engineer - Data Engineering & Streaming Primitives

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.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, rapidly testing 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 is about empowering enterprises to achieve their full potential, and people too. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology and careers to the next level.We are hiring an AI Research Scientist (New Grad) for our AI Research team. Our team is pushing the frontier of autonomous, self-improving AI systems — building agents that reason, code, and learn at scale inside the Snowflake Data Cloud. This role sits at the intersection of agentic AI and reinforcement learning, where your research will directly shape how enterprises leverage intelligent automation.<h2>AS AN AI RESEARCH SCIENTIST AT SNOWFLAKE, YOU WILL:</h2><ul><li>Design and develop agentic frameworks powered by recursive self-improvement loops, enabling AI systems that iteratively refine their own capabilities and strategies</li><li>Build and evaluate auto research agents — systems capable of autonomously formulating hypotheses, executing experiments, and synthesizing findings</li><li>Develop coding agents that understand, generate, and debug code across complex, multi-step programming tasks</li><li>Conduct research in reinforcement learning with a focus on RLHF, DPO, and PPO as mechanisms for aligning and improving agentic behaviors</li><li>Contribute to multi-agent systems where specialized agents collaborate, negotiate, and self-organize to solve enterprise-scale problems</li><li>Develop and curate training data pipelines — both synthetic and human-annotated — to support novel agentic and RL research domains</li><li>Publish research findings at top-tier venues such as NeurIPS, ICML, ICLR, and ACL</li></ul><h2>OUR IDEAL AI RESEARCH SCIENTIST WILL HAVE:</h2><ul><li>PhD in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field (completing or recently completed; or equivalent research experience)</li><li>Foundational expertise in reinforcement learning algorithms, including RLHF, DPO, PPO, or multi-agent systems</li><li>Research experience in LLM post-training, fine-tuning, or reasoning model development</li><li>Demonstrated ability to implement and experiment with agentic architectures — including tool-use, planning, and self-correction loops</li><li>Proficiency in Python and at least one deep learning framework (PyTorch or JAX strongly preferred)</li><li>Strong mathematical and analytical foundation — comfortable working at the intersection of theory and empirical research</li><li>At least one first-author or co-authored publication or preprint in a relevant AI/ML area</li></ul><h2>BONUS POINTS FOR THE FOLLOWING:</h2><ul><li>Hands-on experience building or evaluating coding agents or auto research agents</li><li>Familiarity with recursive self-improvement frameworks or automated AI scientist paradigms</li><li>Experience with large-scale distributed training or efficient training paradigms</li><li>Background in mathematical reasoning, structured decision-making, or program synthesis</li><li>Exposure to domain-specific AI applications in healthcare, finance, or enterprise workflows</li></ul><h2>WHY JOIN OUR AI RESEARCH TEAM AT SNOWFLAKE?</h2>Snowflake's AI Research team operates at the frontier of what autonomous AI systems can do — not as a research lab disconnected from practice, but as a team where your work ships into a platform used by thousands of enterprises. You'll be working alongside researchers and engineers who are building the next generation of agentic infrastructure, with access to large-scale compute, real-world data challenges, and the shortest possible path from research idea to product impact.For a new grad role, this is a rare opportunity to grow your research career while contributing to systems that actually run in production — shaping how AI agents reason, learn, and improve themselves inside the world's leading data cloud.Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.How do you want to make your impact?For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: <a target="_blank" rel="noopener noreferrer ugc" href="http://careers.snowflake.com">careers.snowflake.com</a>

AI Research Scientist, New Grad – Agents & Reinforcement Learning

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.<h2>About the Role</h2>We are hiring a Senior Software Engineer for our Data Platform team - the team that owns the core streaming execution and database internals powering Snowflake's platform. You'll work deep in the stack: stream processing runtimes, query execution engines, storage layers, and the distributed systems primitive that everything else is built on.<h2>AS A SOFTWARE ENGINEER, DATA PLATFORM AT SNOWFLAKE, YOU WILL:</h2><ul><li>Design and implement high-throughput stream processing systems with strong correctness guarantees - exactly-once semantics, out-of-order event handling, low-latency execution</li><li>Work on database internals - query execution, operator design, storage engine components, or transaction processing at cloud scale</li><li>Own features and systems end-to-end: design, implementation, testing, deployment, and production observability</li><li>Drive architectural decisions that shape the long-term evolution of Snowflake's streaming and core platform layers</li><li>Mentor engineers through design reviews, code reviews, and technical guidance</li><li>Partner across product, infrastructure, and research teams to deliver high-impact, foundational capabilities</li></ul><h2>OUR IDEAL CANDIDATE WILL HAVE:</h2><ul><li>5+ years of software engineering experience in distributed systems, query engines, streaming infrastructure, or database internals (or equivalent, including research)</li><li>BS/MS/PhD in Computer Science or related field - graduate research in streaming systems, query processing, or database engines is a strong differentiator</li><li>Deep expertise in distributed systems: consistency, fault tolerance, replication, state management</li><li>Hands-on experience with stream processing systems - building, operating, or extending them (industry or academic)</li><li>Proficiency across multiple languages such asJava, Scala, C++, and Python, with a track record of production systems at scale</li><li>Proficiency with AI-native software engineering and agentic development workflows</li></ul>Ability to lead complex technical projects independently with minimal direction<h2>BONUS POINTS FOR:</h2><ul><li>Experience with stream processing engine internals (e.g., state backends, checkpointing, runtime, or operator development) in systems like Apache Flink, Spark Structured Streaming, or similar.</li><li>Experience with SQL engine internals: query optimization, execution plan design, storage formats, or transaction layers</li><li>Published research or thesis work in streaming, real-time query processing, or distributed computation</li><li>Contributions to open-source data infrastructure or database systems</li><li>Familiarity with Spec Driven Development (SDD) and Test Driven Development (TDD)</li><li>Familiarity with formal verification</li></ul>Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.How do you want to make your impact?For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: <a target="_blank" rel="noopener noreferrer ugc" href="http://careers.snowflake.com">careers.snowflake.com</a>

Senior Software Engineer, Data Transformation

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.We are hiring a Post-Doctoral Researcher for our AI Research team. This 24 month fixed-term position is designed for recent PhD graduates looking to deepen their research experience on challenging problems at the frontier of AI — specifically, applying machine learning to high-impact real-world domains like medicine, finance, and law. You'll collaborate closely with Snowflake researchers, scientists, and engineers on fundamental and applied problems, publishing high-quality work while helping shape how AI integrates with the world's most consequential industries.<h2>AS A POST-DOCTORAL RESEARCHER AT SNOWFLAKE, YOU WILL:</h2><ul><li>Collaborate with research mentors to formulate research projects or novel applications of machine learning aligned with the team's mission, with a focus on AI applied to medicine, finance, or law</li><li>Conduct independent and collaborative research and publish high-quality work at top AI and domain-applied research venues</li><li>Design and execute large-scale experiments using modern deep learning frameworks, writing high-quality, reusable code</li><li>Develop models and systems that bridge AI capabilities with real-world application requirements in high-stakes, regulated domains</li><li>Engage across teams — including with domain experts and applied engineering — to ground research in practical constraints and real-world impact</li><li>Contribute to the broader research community through publications, open-source releases, and collaboration with academic and industry partners</li></ul><h2>OUR IDEAL POST-DOCTORAL RESEARCHER WILL HAVE:</h2><ul><li>PhD (or expected completion by start date) in Computer Science, Statistics, Mathematics, or a related STEM field, or equivalent practical experience</li><li>Research experience in machine learning or AI techniques (e.g., open-source projects, campus lab experience, research internships, or publications)</li><li>Proficiency in Python and experience training deep learning models using PyTorch, JAX, TensorFlow, or equivalent frameworks</li><li>One or more scientific publication submissions in top AI or applied domain research venues (e.g., NeurIPS, ICML, ICLR, AAAI, ACL — or equivalent high-quality venues in medicine, finance, or law)</li><li>Ability to work independently and collaborate effectively across research teams and domain experts</li></ul><h2>BONUS POINTS FOR THE FOLLOWING:</h2><ul><li>Research background at the intersection of AI and one or more of: medicine (clinical NLP, medical imaging, drug discovery), finance (quantitative modeling, risk, forecasting, market analysis), or law (legal NLP, contract analysis, reasoning, compliance)</li><li>Experience designing, fine-tuning, or evaluating LLMs or foundation models in applied domain settings</li><li>Familiarity with evaluation challenges in high-stakes AI — fairness, explainability, robustness, or regulatory constraints</li><li>Publications at domain-applied AI venues (e.g., CHIL, ML4H, FinNLP, NLLP)</li><li>Experience with retrieval-augmented generation (RAG), knowledge graphs, or structured reasoning over domain-specific data</li></ul>Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.How do you want to make your impact?For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: <a target="_blank" rel="noopener noreferrer ugc" href="http://careers.snowflake.com">careers.snowflake.com</a>

Post-Doctoral Researcher (Fixed-Term)

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.<h2>Senior Software Engineer — Cortex Training</h2>The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput.The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast &amp; sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it.<h2>YOU WILL:</h2><ul><li>Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane.</li><li>Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional GPU pools, with fault tolerance built in.</li><li>Drive end-to-end performance at scale — keep the training, inference, and RL loops fast and the data plane responsive under heavy concurrent load, with GPUs kept saturated.</li><li>Productionize research building blocks — partner with Snowflake Research to turn state-of-the-art training and inference techniques into reliable, composable components customers can run at enterprise scale.</li></ul><h2>QUALIFICATIONS:</h2><ul><li>3 + years (Intermediate) | 6+ years (Senior) building and shipping production ML systems</li><li>Strong distributed systems and infrastructure foundation — designing scalable, fault-tolerant services and operating them on Kubernetes in production.</li><li>Familiarity with GPU and LLM infrastructure — e.g., PyTorch, DeepSpeed/FSDP, Ray, CUDA/NCCL, vLLM; able to debug across the data, infrastructure, and GPU layers.</li><li>Demonstrated ability to harden complex systems for reliability, throughput, and cost efficiency.</li><li>BS in Computer Science or a related field (MS/PhD a plus).</li><li>(Bonus) Hands-on LLM post-training / modeling experience — the strongest candidates pair deep infra skills with real post-training intuition.</li></ul>Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.How do you want to make your impact?For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: <a target="_blank" rel="noopener noreferrer ugc" href="http://careers.snowflake.com">careers.snowflake.com</a>

Snowflake

Open jobs at Snowflake

Prinicpal Software Engineer - Data Engineering & Streaming Primitives

AI Research Scientist, New Grad – Agents & Reinforcement Learning

Senior Software Engineer, Data Transformation

Post-Doctoral Researcher (Fixed-Term)

Senior Software Engineer - Cortex Training

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