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 looking for people who have a strong background in data science and cloud architecture to join our AI/ML Workload Services team to create exciting new offerings and capabilities for our customers! This team within the Services Delivery group will be working with customers using Snowflake to expand their use of the Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be highly technical and hands-on, where you will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators.
AS A SR. TECHNICAL ARCHITECT, AI/ML AT SNOWFLAKE, YOU WILL:Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload
Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements
Work hands-on where needed using SQL, Python, and APIs to build POCs that demonstrate implementation techniques and best practices on Snowflake technology for GenAI and ML workloads
Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them
Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
Provide guidance on how to resolve customer-specific technical challenges
Support other members of the Services Delivery team develop their expertise
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing
Ability and flexibility to travel to work with customers on-site 25% of the time
Minimum 10 years experience working with customers in a pre-sales or post-sales technical role
Skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models
Experience and understanding of at least one public cloud platform (AWS, Azure or GCP)
Experience with at least one Data Science tool such as Sagemaker, AzureML, Vertex, Dataiku, DataRobot, H2O, and Jupyter Notebooks
Experience with Large Language Models, Retrieval and Agentic frameworks
Hands-on scripting experience with SQL and at least one of the following; Python, R, Java or Scala.
Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar
University degree in computer science, engineering, mathematics or related fields, or equivalent experience
Experience with Generative AI, LLMs and Vector Databases.
Experience with Databricks/Apache Spark, including PySpark
Experience implementing data pipelines using ETL tools
Experience working in a Data Science role
Proven success at enterprise software
Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc
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: careers.snowflake.com
Skills Required
- Minimum 10 years experience working with customers in a pre-sales or post-sales technical role
- Deep technical expertise with Snowflake for AI/ML workloads
- Hands-on scripting with SQL and at least one of: Python, R, Java, or Scala
- Experience with Data Science lifecycle: feature engineering, model development, deployment, and management
- Strong understanding of MLOps, model deployment and monitoring
- Experience with at least one public cloud platform (AWS, Azure, or GCP)
- Experience with at least one Data Science tool (SageMaker, AzureML, Vertex, Dataiku, DataRobot, H2O, Jupyter Notebooks)
- Experience with Large Language Models, retrieval and agentic frameworks
- Experience with libraries such as Pandas, PyTorch, TensorFlow, Scikit-Learn (or similar)
- University degree in computer science, engineering, mathematics or equivalent experience
- Experience with Generative AI, LLMs and Vector Databases
- Experience with Databricks/Apache Spark, including PySpark
- Experience implementing data pipelines using ETL tools
- Proven success at enterprise software and vertical expertise (FSI, Retail, Manufacturing etc.)
- Prior experience working in a data science role
Snowflake Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snowflake and has not been reviewed or approved by Snowflake.
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Fair & Transparent Compensation — Pay is considered competitive across many roles, and the company highlights structured practices aimed at pay equity. Total compensation is often described as strong at senior levels when equity and bonuses are included.
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Equity Value & Accessibility — Equity grants and an ESPP are standard, making ownership accessible and a meaningful part of total rewards. New-hire RSUs and ongoing equity alongside bonus/commission programs are emphasized.
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Healthcare Strength — Comprehensive medical coverage is offered with programs like Lyra providing up to 25 no-cost therapy/coaching sessions, alongside HSA-eligible plans. Wellness resources and additional clinical programs (such as Omada for certain conditions) broaden the scope of support.
Snowflake Insights
What We Do
Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.
Why Work With Us
Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.
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