Solutions Architect – AI/ML
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Job Description
About Snowflake:
Snowflake is a rapidly growing company scaling its team to accelerate growth. They are seeking individuals who share their values, challenge conventional thinking, and drive innovation. A core component of their work involves handling sensitive data, and employees are expected to adhere strictly to confidentiality and security standards.
Job Description: Solutions Architect – AI/ML
This role is within Snowflake’s Professional Services team, focusing on the development of new offerings and capabilities for customers utilizing the Snowflake Data Cloud. The position is highly strategic, advising clients on best practices for implementing data science workloads on Snowflake.
Responsibilities:
• Technical Expertise: Serve as a technical expert on all aspects of Snowflake related to AI/ML workloads.
• Best Practices & Advice: Provide customers with best practices and guidance on data science workloads within the Snowflake environment.
• Pipeline Development: Build and deploy ML pipelines using Snowflake features and/or partner tools based on customer requirements.
• Hands-on Development: Engage in hands-on development using SQL and Python to create proofs-of-concept (POCs) showcasing implementation techniques and best practices.
• Knowledge Transfer: Ensure knowledge transfer to empower customers to independently extend Snowflake’s capabilities.
• Competitive Landscape: Maintain a deep understanding of competitive and complementary AI/ML technologies and vendors, and how to position Snowflake effectively.
• System Integrator Collaboration: Work closely with System Integrator consultants to successfully deploy Snowflake in customer environments.
• Technical Problem Solving: Provide guidance on resolving customer-specific technical challenges.
• Team Development: Support other Professional Services team members in developing their expertise.
• Product Improvement: Collaborate with Product Management, Engineering, and Marketing teams to enhance Snowflake’s products and marketing strategies.
Required Qualifications:
• University degree in data science, computer science, engineering, mathematics, or a related field, or equivalent experience.
• Minimum 6 years’ experience working with customers in a pre-sales or post-sales technical role.
• Excellent presentation skills to both technical and executive audiences, adaptable to various formats (whiteboard, presentations, demos).
• Comprehensive understanding of the entire data science lifecycle (feature engineering, model development, deployment, and 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).
• Experience with at least one data science tool (e.g., AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, 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.
Bonus Qualifications:
• Experience with Generative AI, LLMs, and Vector Databases.
• Experience with Databricks/Apache Spark.
• Experience implementing data pipelines using ETL tools.
• Experience working in a Data Science role.
• Proven success at enterprise software.
• Vertical expertise in a core vertical (e.g., FSI, Retail, Manufacturing).
Compensation and Benefits:
The estimated base salary range is $150,000 – $210,000, plus participation in Snowflake’s bonus and equity plan. A competitive benefits package is also offered.