Snowflake AI/ML Sr Solutions Architect
Posted 2 days ago by 1764148430
Negotiable
Outside
Remote
USA
Summary: The Snowflake AI/ML Sr Solutions Architect is responsible for providing technical expertise on Snowflake for AI/ML workloads, advising customers on best practices, and building ML pipelines. The role involves hands-on work with SQL and Python to create proofs of concept and ensuring knowledge transfer to customers. Additionally, the architect will collaborate with various teams to enhance Snowflake's offerings and address customer-specific technical challenges. This position requires extensive experience in data science and customer engagement in technical roles.
Key Responsibilities:
- Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
- Provide customers with best practices and advice related to Data Science workloads on Snowflake.
- Build and deploy ML pipelines using Snowflake features and/or ecosystem partner tools based on customer requirements.
- Work hands-on using SQL and Python to build POCs demonstrating implementation techniques and best practices.
- Ensure knowledge transfer to enable customers to extend Snowflake capabilities independently.
- Maintain a deep understanding of competitive and complementary technologies in the AI/ML space.
- Work with System Integrator consultants to position and deploy Snowflake in customer environments.
- Provide guidance on resolving customer-specific technical challenges.
- Support Professional Services team members in developing their expertise.
- Collaborate with Product Management, Engineering, and Marketing to improve Snowflake's products and marketing.
Key Skills:
- University degree in data science, computer science, engineering, mathematics, or related fields, or equivalent experience.
- 12-14 years of experience in a pre-sales or post-sales technical role.
- Outstanding presentation skills to technical and executive audiences.
- Thorough understanding of the complete Data Science life-cycle.
- Strong understanding of MLOps and methodologies for deploying and monitoring models.
- Experience with at least one public cloud platform (AWS, Azure, or Google Cloud Platform).
- Experience with Data Science tools such as AWS SageMaker, AzureML, Dataiku, Datarobot, H2O, and Jupyter Notebooks.
- Hands-on scripting experience with SQL and at least one of Python, Java, or Scala.
- Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn, or similar.
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Job Title: Snowflake AI/ML Sr Solutions Architect
Location: 100% remote
Duration: 12 Month Contract
Job Description
AI/ML ARCHITECT
Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake
Build and deploy ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements.
Work hands-on where needed using SQL, Python, to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the Data Science 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
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 Professional Services team develop their expertise.
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake s products and marketing.
Skills: Cortex Analyst, Cortex Search, Snowflake Intelligence
Requirements
University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience.
12-14 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 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 Google Cloud Platform).
Experience with at least one Data Science tool such as AWS Sage maker, AzureML, Dataiku, Datarobot, H2O, and Jupyter Notebooks.
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 or similar.