Snowflake AI/ML Senior Solutions Architect

Job Title: Snowflake AI/ML Senior Solutions Architect
Type: Contract
Location: New York, NY (Onsite required talent preferred to be reside locally)

About the Role

Seeking a seasoned Snowflake AI/ML Solutions Architect to drive technical leadership for AI/ML workloads in enterprise environments. The role focuses on designing, implementing, and optimizing advanced data science solutions leveraging Snowflake s platform and ecosystem. Ideal candidates bring deep hands-on expertise, a strong customer orientation, and fluency in the modern AI/ML stack.

Responsibilities

• Serve as the technical authority for Snowflake s AI/ML capabilities, guiding customers and partners on all aspects of data science workloads.
• Advise on best practices for building and deploying scalable ML pipelines using Snowflake features and partner tools.
• Develop proof-of-concept solutions and demos using SQL and Python to demonstrate end-to-end data science life cycles within Snowflake.
• Ensure effective knowledge transfer, enabling customers to independently scale and manage data science/ML solutions.
• Maintain up-to-date understanding of key technologies and vendors in the AI/ML ecosystem to competitively position Snowflake.
• Collaborate closely with System Integrators and internal teams to enable successful deployment and integration in client environments.
• Troubleshoot and resolve customer-specific technical challenges related to AI/ML workloads.
• Mentor Professional Services colleagues, elevating team expertise.
• Coordinate with Product Management, Engineering, and Marketing to help shape Snowflake s evolving capabilities.
• Execute replatforming initiatives, such as migrating chat bots to Snowflake Cortex Analyst and integrating unstructured data search.
• Support the integration and enhancement of existing predictive ML models into new Snowflake-based solutions.

Required Qualifications

• Bachelor s or advanced degree in Data Science, Computer Science, Engineering, Mathematics or a related discipline, or equivalent experience.
• 12 14 years experience in technical roles supporting customers pre-sales or post-sales.
• Exceptional communication ability with both technical and executive audiences.
• Strong grasp of the full data science lifecycle, including model development, deployment, management, and monitoring.
• Proficient in MLOps, with experience in deploying and monitoring AI models.
• Deep familiarity with at least one public cloud (AWS, Azure, or Google Cloud Platform).
• Hands-on experience with data science platforms (e.g., AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, Jupyter Notebooks).
• Solid scripting skills in SQL and at least one language: Python, Java, or Scala.
• Expertise with data science libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn, or similar.

Preferred Qualifications

• Experience with Generative AI, LLMs, and Vector Databases.
• Familiarity with Databricks and Apache Spark.
• Background in building data pipelines with ETL tools.
• Direct experience in Data Science functions.
• Success supporting enterprise software solutions.
• Vertical domain expertise (e.g., Financial Services, Retail, Manufacturing).