Senior Solutions Architect – AI/ML

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🔥 2 hours ago

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Snowflake

5001 - 10000 employees

Founded 2012

☁️ SaaS

🏢 Enterprise

🤝 B2B

SaaS • Enterprise • B2B

Snowflake is a cloud-based data platform and data warehouse-as-a-service. It enables organizations to store, process, analyze, and share large volumes of structured and semi-structured data across multiple clouds, with separated scalable compute and storage, built-in security and data-sharing capabilities, and support for analytics and machine-learning workloads. Snowflake is delivered as a managed SaaS offering for enterprise customers and is primarily marketed and sold as a B2B product.

📋 Description

• Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflakes technology stack. • Work with customers to understand their AI/ML use case, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery. • Understand how to build, deploy and AI and ML pipelines using Snowflake features and/or Snowflake ecosystem based on customer requirements. • Work hands-on where needed using SQL, Python, and Cortex AI features to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the AI/ML workload. • 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 • 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.

🎯 Requirements

• Minimum 5 years experience working with customers in a pre-sales or post-sales technical role. • Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos • Thorough understanding of the common generative AI and agent lifecycles including document ingestion, vector embedding selection, llm selection and optimization, genAI monitoring and evaluation techniques. • Thorough understanding of the complete ML life-cycle including feature engineering, model development, model deployment and model management. • Strong understanding of AI/MLOps, coupled with technologies and methodologies for deploying and monitoring models and agents. • Experience and understanding of at least one public cloud platform (AWS, Azure or GCP) • Experience with at least one AI/ML platform such as AWS Sagemaker, Databricks, GCP and Vertex AI, AzureML, Dataiku, Datarobot, etc. • Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala. • Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn, LangChain/LangGraph, LlamaIndex or similar. • University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience

🏖️ Benefits

• medical, dental, vision, life, and disability insurance • 401(k) retirement plan • flexible spending & health savings account • at least 12 paid holidays • paid time off • parental leave • employee assistance program • other company benefits

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