Snowflake

1 week ago

Sr. Technical Architect, AI/ML

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Design and deliver AI/ML solutions for customers using Snowflake’s Data Cloud. You’ll build and deploy ML pipelines and GenAI POCs with SQL, Python, and APIs, and partner with customer and Systems Integrator teams to coordinate requirements through deployment. As a Snowflake technical expert, you’ll lead knowledge transfer, troubleshoot customer technical challenges, and help position Snowflake against competitive AI/ML offerings while traveling on-site ~25% of the time.

Location: Australia

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Serve as a technical expert on Snowflake for the AI/ML workload and help position Snowflake versus competitive technologies.
•Build, deploy, and operationalize ML pipelines using Snowflake features and/or partner ecosystem tools based on customer requirements.
•Create hands-on SQL/Python/APIs POCs for GenAI and ML workloads and demonstrate implementation techniques and best practices.
•Collaborate with customer teams and Systems Integrators to coordinate solution design through deployment, and provide guidance resolving customer technical challenges.
•Ensure knowledge transfer so customers can extend capabilities, and collaborate with Product Management, Engineering, and Marketing to improve offerings.

Travel: Medium travel

Key Requirements

•Minimum 10 years of experience working with customers in a pre-sales or post-sales technical role.
•Thorough understanding of the complete Data Science life-cycle (feature engineering, model development, deployment, and model management).
•Strong understanding of MLOps, including technologies and methodologies for deploying and monitoring models.
•Experience with at least one public cloud platform (AWS, Azure, or GCP) and at least one data science tool (e.g., SageMaker, AzureML, Vertex, Dataiku, DataRobot, H2O, Jupyter).
•Hands-on scripting with SQL and at least one of Python, R, Java, or Scala, plus experience with libraries such as Pandas, PyTorch, TensorFlow, or SciKit-Learn.

Experience:10+ yearsData scienceCloud architectureMLOpsAI/MLEnterprise software

Education:Bachelor's

Skills:PresentingKnowledge transferCollaborationProblem-solvingTechnical communication

Tech Stack:SnowflakeSQLPythonAPIsAWSAzureGCPSageMakerAzureMLVertexDataikuDataRobotH2OJupyter NotebooksLarge Language ModelsRetrievalAgentic frameworksPandasPyTorchTensorFlow

Company Brief

Snowflake

Provides a cloud-native data platform for data warehousing, data engineering, data science, and analytics, enabling organizations to store, process, and share large-scale data across multiple cloud providers with elastic scalability and performance.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bozeman, United States

Founded: 2012

Website LinkedIn

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Snowflake

1 week ago

Sr. Technical Architect, AI/ML

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Australia

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Serve as a technical expert on Snowflake for the AI/ML workload and help position Snowflake versus competitive technologies.
•Build, deploy, and operationalize ML pipelines using Snowflake features and/or partner ecosystem tools based on customer requirements.
•Create hands-on SQL/Python/APIs POCs for GenAI and ML workloads and demonstrate implementation techniques and best practices.
•Collaborate with customer teams and Systems Integrators to coordinate solution design through deployment, and provide guidance resolving customer technical challenges.
•Ensure knowledge transfer so customers can extend capabilities, and collaborate with Product Management, Engineering, and Marketing to improve offerings.

Travel: Medium travel

Key Requirements

•Minimum 10 years of experience working with customers in a pre-sales or post-sales technical role.
•Thorough understanding of the complete Data Science life-cycle (feature engineering, model development, deployment, and model management).
•Strong understanding of MLOps, including technologies and methodologies for deploying and monitoring models.
•Experience with at least one public cloud platform (AWS, Azure, or GCP) and at least one data science tool (e.g., SageMaker, AzureML, Vertex, Dataiku, DataRobot, H2O, Jupyter).
•Hands-on scripting with SQL and at least one of Python, R, Java, or Scala, plus experience with libraries such as Pandas, PyTorch, TensorFlow, or SciKit-Learn.

Experience:10+ yearsData scienceCloud architectureMLOpsAI/MLEnterprise software

Education:Bachelor's

Skills:PresentingKnowledge transferCollaborationProblem-solvingTechnical communication

Tech Stack:SnowflakeSQLPythonAPIsAWSAzureGCPSageMakerAzureMLVertexDataikuDataRobotH2OJupyter NotebooksLarge Language ModelsRetrievalAgentic frameworksPandasPyTorchTensorFlow

Company Brief

Snowflake

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bozeman, United States

Founded: 2012

Website LinkedIn