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 a commitment to data security and confidentiality, requiring all employees to adhere to strict standards.
Job Description: Solutions Architect – AI/ML
This role is within Snowflake’s Professional Services team, focused on building new offerings and capabilities for customers utilizing the Snowflake Data Cloud. The team works with clients to expand their use of the data cloud, guiding them through the entire data science pipeline—from concept to deployment and beyond. The position is strategic, advising clients on best practices for implementing AI/ML 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 Snowflake.
• Pipeline Development: Build and deploy ML pipelines leveraging Snowflake features and/or partner ecosystem tools based on client needs.
• Hands-on Development: Work directly with SQL and Python (and potentially Java or Scala) to create Proofs of Concept (POCs) demonstrating implementation techniques and best practices.
• Knowledge Transfer: Ensure knowledge transfer to clients, empowering them to independently extend Snowflake’s capabilities.
• Competitive Analysis: 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 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 Skills & Experience:
• 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.
• Exceptional presentation skills to both technical and executive audiences (both impromptu and formal 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 language (Python, Java, or Scala).
• Experience with relevant libraries (e.g., Pandas, PyTorch, TensorFlow, SciKit-Learn).
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 sales.
• Vertical expertise in a specific industry (e.g., FSI, Retail, Manufacturing).
Compensation & Benefits:
• Estimated base salary range: $150,000 – $210,000.
• Bonus and equity plan eligibility.
• Comprehensive benefits package including medical, dental, vision, life, and disability insurance; 401(k); flexible spending & health savings accounts; paid time off; parental leave; and more.
