Sr. Technical Architect AI/ML

About the role

Join Snowflake's AI/ML Workload Services team, a dedicated part of the Services Delivery group, to help customers expand and optimize their use of the Data Cloud platform. This role is focused on bringing data science pipelines from initial concept through to deployment, leveraging Snowflake's advanced features and its extensive partner ecosystem. You will be a hands-on technical expert responsible for designing innovative solutions, guiding customer teams, and collaborating with System Integrators to ensure successful implementations. The position requires deep technical knowledge, strong communication skills, and the ability to work closely with clients to address complex AI and ML challenges.

Key facts

What you'll do

• Serve as a technical authority on all aspects of Snowflake related to AI/ML workloads, providing expert guidance to customers and internal teams.
• Design, construct, and deploy machine learning pipelines tailored to customer needs, utilizing Snowflake features or partner tools within the Snowflake ecosystem.
• Develop proof-of-concept projects using SQL, Python, and APIs to demonstrate best practices for Generative AI and machine learning on Snowflake.
• Conduct knowledge transfer sessions with customers, enabling them to independently extend and optimize Snowflake capabilities for their AI/ML initiatives.
• Maintain awareness of competing and complementary AI/ML technologies, positioning Snowflake's offerings effectively within the broader ecosystem.
• Collaborate closely with System Integrator consultants to deploy Snowflake solutions in customer environments, ensuring seamless integration and performance.
• Provide technical guidance and support to resolve specific customer challenges related to AI/ML workloads.
• Support the development and growth of other team members within the Services Delivery group through mentorship and knowledge sharing.
• Work with Product Management, Engineering, and Marketing teams to gather customer feedback, influence product enhancements, and improve outreach efforts.
• Travel up to 25% of the time to engage with customers on-site, delivering presentations, workshops, and deployment support.

Requirements

• At least 10 years of experience in a customer-facing technical role, either pre-sales or post-sales, with a strong focus on AI/ML solutions.
• Proven ability to present complex technical concepts effectively to both technical audiences and executive stakeholders.
• Deep understanding of the entire data science lifecycle, including feature engineering, model development, deployment, and ongoing management.
• Strong grasp of MLOps principles, including technologies and methods for deploying, monitoring, and maintaining machine learning models in production environments.
• Hands-on experience with at least one major public cloud platform such as AWS, Azure, or GCP.
• Familiarity with data science tools like Sagemaker, AzureML, Vertex AI, Dataiku, DataRobot, H2O, or Jupyter Notebooks.
• Practical experience working with Large Language Models (LLMs), Retrieval frameworks, and Agentic AI architectures.
• Scripting skills in SQL and at least one of the following programming languages: Python, R, Java, or Scala.
• Experience with relevant libraries such as Pandas, PyTorch, TensorFlow, or SciKit-Learn.
• Educational background in computer science, engineering, mathematics, or a related field, or equivalent practical experience.

Nice to have

• Experience working with Generative AI, large language models (LLMs), and Vector Databases.
• Familiarity with Databricks or Apache Spark, including PySpark.
• Experience designing and implementing data pipelines using ETL tools.
• Prior experience in a dedicated Data Science role, contributing to enterprise AI projects.
• Demonstrated success with enterprise software solutions, especially in AI/ML contexts.
• Industry-specific expertise in sectors such as Financial Services Industry (FSI), Retail, or Manufacturing.

Skills & tools

• SQL
• Python
• R
• Java
• Scala
• APIs
• AWS
• Azure
• GCP
• Sagemaker
• AzureML
• Vertex AI
• Dataiku
• DataRobot
• H2O.ai
• Jupyter Notebooks
• Pandas
• PyTorch
• TensorFlow
• SciKit-Learn
• Databricks/Apache Spark
• PySpark
• ETL tools
• Large Language Models (LLMs)
• Generative AI
• Vector Databases
• Retrieval frameworks
• Agentic frameworks

Practical notes

• This role is based in Australia, Victoria, and is on-site, requiring physical presence at the designated location.
• The position involves travel up to 25% for on-site customer engagements, including delivering workshops, presentations, and deployment support.
• Compensation details for US-based roles can be found on the Snowflake Careers Site, but specific salary and benefits information are not disclosed in this listing.
• The role emphasizes technical expertise, customer interaction, and collaboration with cross-functional teams to drive AI/ML initiatives on Snowflake.
• Candidates should be prepared to work in a fast-paced environment, with a focus on innovative solutions and customer success.

About the company

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