Responsibilities
- Act as a technical expert on Snowflake for AI/ML workloads.
- Build and deploy ML pipelines using Snowflake features and ecosystem partner tools based on customer requirements.
- Use SQL, Python, and APIs to create proofs of concept demonstrating GenAI and ML implementation techniques and best practices.
- Provide knowledge transfer and enable customers to extend Snowflake capabilities independently.
- Maintain expertise in competitive and complementary AI/ML technologies and vendors and position Snowflake accordingly.
- Work deeply with systems integrator consultants to position and deploy Snowflake in customer environments.
- Guide customers through customer-specific technical challenges.
- Support Services Delivery team members in developing their expertise.
- Collaborate with Product Management, Engineering, and Marketing to improve Snowflake products and marketing.
- Travel onsite to work with customers approximately 25% of the time.
Requirements
- At least 10 years of experience working with customers in a pre-sales or post-sales technical role.
- Ability to present technical concepts and solutions to technical and executive audiences using whiteboards, presentations, and demonstrations.
- Thorough understanding of the data science lifecycle, including feature engineering, model development, model deployment, and model management.
- Strong understanding of MLOps and technologies for deploying and monitoring models.
- Experience with 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, or Jupyter Notebooks.
- Experience with large language models, retrieval, and agentic frameworks.
- Hands-on scripting experience with SQL and at least one of Python, R, Java, or Scala.
- Experience with libraries such as Pandas, PyTorch, TensorFlow, or Scikit-learn.
- University degree in computer science, engineering, mathematics, or a related field, or equivalent experience.
- Bonus: experience with Generative AI, LLMs, and vector databases.
- Bonus: experience with Databricks, Apache Spark, and PySpark.
- Bonus: experience implementing data pipelines with ETL tools.
- Bonus: experience in a data science role, enterprise software, or a core vertical such as financial services, retail, or manufacturing.
Benefits
- Travel to customer sites approximately 25% of the time.
- Salary and benefits information is provided on the Snowflake Careers Site for United States roles.
Tech Stack
Categories
About Snowflake
**Snowflake is proud to be the Official Data Collaboration Provider for LA28 and Team USA.** Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.