Senior Artificial Intelligence/Machine Learning Architect

Who you are

• 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud
• Familiarity and associated knowledge of generative AI techniques like RAG, few shot learning, prompt engineering, or fine-tuning that are used to operationalize enterprise AI use cases like interactive chat applications or text processing
• Deep knowledge of Python and common ML packages (such as LangChain, pandas, sklearn, and PyTorch) as well as data engineering tools and technologies like dbt, Airflow, and Spark
• Strong presentation skills to both technical and executive audiences, whether whiteboarding sessions or formal readouts and demos
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages
• Experience and understanding of large-scale infrastructure-as-a-service platforms (e.g. AWS, Microsoft Azure, GCP, etc.)
• 1+ years of practical Snowflake experience
• Knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum, etc.)

What the job involves

• Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud
• This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions
• Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas
• Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases
• Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback
• Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos
• Influence, tailor and maintain Sales Engineering AI and ML selling assets, including customer presentations, demonstrations, and customer stories

Benefits

• Comprehensive health insurance plans
• Health savings accounts
• Robust retirement plans
• Life and disability insurance
• Weekly online lunch and learns
• Virtual workout classes
• Ergonomic work-from-home equipment
• On-demand mental health and wellness programs
• Fertility benefits and family planning resources
• Generous time-off and various leave plans
• Onsite and Remote Work
• Employee discounts and pre-tax selections
• New hire equity + Employee Stock Purchase Plan (ESPP)
• Quarterly bonus or commission program