Senior Technical Architect – AI/ML

🔥 0 minutes ago

🔔 Pennsylvania – Remote

🔔 Pennsylvania – Remote

💵 $136k - $178.5k / year

⏰ Full Time

🟠 Senior

🔙 Backend Engineer

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Snowflake

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2012

☁️ SaaS

🏢 Enterprise

🤝 B2B

SaaS • Enterprise • B2B

Snowflake is a cloud-based data platform and data warehouse-as-a-service. It enables organizations to store, process, analyze, and share large volumes of structured and semi-structured data across multiple clouds, with separated scalable compute and storage, built-in security and data-sharing capabilities, and support for analytics and machine-learning workloads. Snowflake is delivered as a managed SaaS offering for enterprise customers and is primarily marketed and sold as a B2B product.

📋 Description

• Design robust, scalable AI/ML solutions using the full Snowflake native stack and partner ecosystem • Perform deep-dive Root Cause Analysis for complex system dependencies in AI/ML solutions • Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI • Mentor Level 3 architects on MLOps and architectural design best practices • Deconstruct failures in complex pipelines involving external cloud services • Analyze potential failure modes, including model drift and data skew, early in the lifecycle • Architect data security and access controls for sensitive AI/ML training data • Reduce post-deployment technical debt • Drive regional success of complex implementations • Contribute to peer mentorship impact and strategic outcomes

🎯 Requirements

• Minimum of 8 years of related experience • Bachelor's degree • Expertise in resolving wide-ranging issues in creative ways • Ability to present complex AI/ML concepts and ROI to technical and business audiences • Thorough understanding of the complete Data Science life-cycle, including feature engineering, model development, model deployment, and model management • Experience with Snowflake Model Registry and Cortex Functions • Proficiency in Python • Experience with external MLOps platforms such as Kubeflow or SageMaker • Understanding of distributed systems involving AWS, Azure, or GCP • Knowledge of model drift and data skew failure modes • Ability to architect data security and access controls for sensitive AI/ML training data • Experience with Generative AI, LLMs, and Vector Databases is a bonus • Experience with Databricks or Apache Spark is a bonus • Experience implementing data pipelines using ETL tools is a bonus • Experience working in a Data Science role is a bonus • Proven success at enterprise software is a bonus • Vertical expertise in FSI, Retail, Manufacturing, or similar is a bonus

🏖️ Benefits

• Medical insurance • Dental insurance • Vision insurance • Life insurance • Disability insurance • 401(k) retirement plan • Flexible spending account • Health savings account • At least 12 paid holidays • Paid time off • Parental leave • Employee assistance program • Competitive benefits package • Bonus plan • Equity plan