AI/ML Architect
BambooHRFull Time
Senior (5 to 8 years)
Candidates must possess a minimum of 8 years in a Data Science role with at least 2 production model deployments, and 10 years of customer-facing technical experience in pre-sales or post-sales. A thorough understanding of the complete Data Science lifecycle, including feature engineering, model development, deployment, and management, is essential. Strong knowledge of MLOps, Python scripting with libraries like Pandas, XGBoost, PyTorch, TensorFlow, or SciKit-Learn, and exceptional presentation skills for technical and executive audiences are required. A university degree in data science, mathematics, or a related field, or equivalent experience, is necessary. Experience with Generative AI, LLMs, Vector Databases, Databricks/Apache Spark, data pipelines using ETL tools, and vertical expertise are considered bonus points.
The Solution Innovation Architect will design and build AI/ML demos using the Snowflake platform, collaborating with Product teams to align demo creation with product releases. They will provide technical expertise on Snowflake's AI/ML features to sales engineering teams, demonstrating a strong understanding of the data science modeling lifecycle, Generative AI landscape, and Large Language Models. This role involves staying current with AI/ML advancements, providing thought leadership through external content, and working with large datasets for data quality evaluation, feature engineering, optimization, and MLOps.
Data management and analytics platform
Snowflake provides a platform called the AI Data Cloud that helps organizations manage and analyze their data. This platform allows users to store and process large amounts of data efficiently, offering services like data warehousing, data lakes, data engineering, data science, and data sharing. Snowflake's system works by uniting data from different sources, enabling secure sharing and performing various types of analytics. What sets Snowflake apart from its competitors is its ability to operate seamlessly across multiple public clouds, allowing users to access their data from anywhere. The company's goal is to help businesses leverage their data for better decision-making by providing a flexible subscription-based service that scales according to their needs.