Solutions Architect – AI/ML
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Job Description
About Snowflake:
Snowflake is a rapidly growing company scaling its team to accelerate its growth. They are seeking individuals who share their values, challenge conventional thinking, and drive innovation. They emphasize building a future for both the employee and the company.
Job Description: Solutions Architect – AI/ML
This role is within Snowflake’s Professional Services team, focusing on helping customers expand their use of the Snowflake Data Cloud for data science. The position is strategic, advising clients on best practices for implementing data science workloads on Snowflake. It involves designing solutions, coordinating with customer and Systems Integrator teams, and overseeing project success.
Key Responsibilities:
• Technical Expertise: Serve as a technical expert on all aspects of Snowflake concerning AI/ML workloads.
• Best Practices & Advice: Provide customers with best practices and guidance on data science workloads within Snowflake.
• Pipeline Development: Build and deploy ML pipelines using Snowflake features and/or partner tools based on customer needs.
• Hands-on Development: Work practically with SQL and Python (and potentially Java or Scala) to create proofs-of-concept demonstrating implementation techniques and best practices.
• Knowledge Transfer: Ensure knowledge transfer to customers, empowering them to independently extend Snowflake capabilities.
• Competitive Landscape Understanding: Maintain a deep understanding of competing and complementary AI/ML technologies and vendors, and how to position Snowflake effectively.
• System Integrator Collaboration: Work closely with System Integrator consultants at a technical level to successfully deploy Snowflake in customer environments.
• Technical Problem Solving: Provide guidance on resolving customer-specific technical challenges.
• Team Mentorship: Support other Professional Services team members in developing their expertise.
• Cross-functional Collaboration: Collaborate with Product Management, Engineering, and Marketing teams to improve Snowflake’s products and marketing efforts.
Required Skills and Experience:
• University degree in data science, computer science, engineering, mathematics, or a related field (or equivalent experience).
• Minimum 6 years of experience working with customers in a pre-sales or post-sales technical role.
• Excellent presentation skills to both technical and executive audiences (both formal and impromptu).
• Thorough 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 Points:
• Experience with Generative AI, LLMs, and Vector Databases.
• Experience with Databricks/Apache Spark.
• Experience implementing data pipelines using ETL tools.
• Experience in a Data Science role.
• Proven success in enterprise software.
• Vertical expertise in a specific industry (e.g., FSI, Retail, Manufacturing).
Compensation and Benefits:
The estimated base salary range is $150,000 – $210,000, plus bonus and equity plan participation. A competitive benefits package is also included.
