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. They emphasize a commitment to confidentiality and security in handling sensitive data, making adherence to data security plans a key responsibility for all employees.
Job Description: Solutions Architect – AI/ML
This role within Snowflake’s Professional Services team focuses on helping customers expand their use of the Snowflake Data Cloud for data science. The team works with clients to build data science pipelines, from initial concept to deployment and ongoing maintenance, leveraging Snowflake’s features and its partner ecosystem. The position is strategic, advising clients on best practices for implementing AI/ML workloads on Snowflake.
Responsibilities:
• Serve as a technical expert on all aspects of Snowflake related to AI/ML workloads.
• Provide clients with best practices and guidance on data science workloads within Snowflake.
• Build and deploy ML pipelines using Snowflake features and/or partner tools based on customer requirements.
• Hands-on development using SQL and Python to create proofs-of-concept demonstrating implementation techniques and best practices within the data science workload.
• Follow best practices, including knowledge transfer to enable clients to independently extend Snowflake’s capabilities.
• Maintain a comprehensive understanding of competitive and complementary AI/ML technologies and vendors, and how to position Snowflake effectively.
• Collaborate deeply with System Integrator consultants to successfully deploy Snowflake in client environments.
• Provide guidance on resolving customer-specific technical challenges.
• Mentor other Professional Services team members.
• Collaborate with Product Management, Engineering, and Marketing to improve Snowflake’s products and marketing efforts.
Qualifications:
• 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.
• Exceptional presentation skills to both technical and executive audiences (whiteboarding, 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 like 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 (e.g., FSI, Retail, Manufacturing).
Compensation:
The estimated base salary range is $150,000 – $210,000, plus eligibility for Snowflake’s bonus and equity plan. A competitive benefits package is also included. The starting salary will be determined based on skills, experience, and location.
