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. The company emphasizes confidentiality and security, requiring all employees to adhere to data security standards and handle sensitive data responsibly.
Job Description: Solutions Architect – AI/ML
This role is within Snowflake’s Professional Services team, focused on helping customers expand their use of the Snowflake Data Cloud for data science. The position is highly strategic, advising clients on best practices for implementing data science workloads on Snowflake.
Key Responsibilities:
• Serve as a technical expert on all aspects of Snowflake’s AI/ML capabilities.
• Provide customers with best practices and guidance on data science workloads within the Snowflake environment.
• Build, deploy, and manage ML pipelines using Snowflake features and/or partner tools based on client requirements.
• Develop hands-on proofs-of-concept (POCs) using SQL, Python, and other tools to demonstrate implementation techniques and best practices.
• Ensure knowledge transfer to clients, enabling them to independently utilize Snowflake’s capabilities.
• Maintain a deep understanding of competitive and complementary AI/ML technologies and vendors, and how Snowflake positions itself within the market.
• Collaborate extensively with System Integrator consultants at a technical level.
• Provide guidance on resolving customer-specific technical challenges.
• Mentor and develop other members of the Professional Services team.
• 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 of experience in a pre-sales or post-sales technical role working with clients.
• Excellent presentation skills to both technical and executive audiences (whiteboarding, presentations, demos).
• Thorough understanding of the entire data science lifecycle (feature engineering, model development, deployment, and management).
• Strong understanding of MLOps, including technologies and methodologies for model deployment and monitoring.
• 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 language (Python, Java, or Scala).
• Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn, or similar.
Preferred Qualifications:
• Experience with Generative AI, LLMs, and vector databases.
• Experience with Databricks/Apache Spark.
• Experience implementing data pipelines using ETL tools.
• Prior experience in a data science role.
• Proven success in enterprise software.
• Vertical expertise in a specific industry (e.g., FSI, Retail, Manufacturing).
Compensation:
The estimated base salary range is $150,000 – $210,000, with additional eligibility for bonuses and equity participation. A comprehensive benefits package is also included.
