JOB DESCRIPTIONAI/ML ARCHITECT
- Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
- Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake
- Build and deploy ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements.
- Work hands-on where needed using SQL Python to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the Data Science workload.
- Follow best practices including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
- Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space and how to position Snowflake in relation to them
- Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
- Provide guidance on how to resolve customer-specific technical challenges.
- Support other members of the Professional Services team develop their expertise.
- Collaborate with Product Management Engineering and Marketing to continuously improve Snowflakes products and marketing.
- GenAI - Cortex Search / RAG
REQUIREMENTS
- University degree in data science computer science engineering mathematics or related fields or equivalent experience.
- 12-14 years experience working with customers in a pre-sales or post-sales technical role.
- Outstanding skills presenting to both technical and executive audiences whether impromptu on a whiteboard or using presentations and demos.
- Thorough understanding of the complete Data Science life-cycle including feature engineering model development model deployment and model management.
- Strong understanding of MLOps coupled with technologies and methodologies for deploying and monitoring models.
- Experience and understanding of at least one public cloud platform (AWS Azure or GCP).
- Experience with at least one Data Science tool such as AWS Sagemaker AzureML Dataiku Datarobot H2O and Jupyter Notebooks.
- Hands-on scripting experience with SQL and at least one of the following; Python Java or Scala.
- Experience with libraries such as Pandas PyTorch TensorFlow SciKit-Learn or similar.
BONUS POINTS FOR HAVING :
- Experience with GenerativeAI LLMs and Vector Databases.
- Experience with Databricks/Apache Spark.
- Experience implementing data pipelines using ETL tools.
- Experience working in a Data Science role.
- Proven success at enterprise software.
- Vertical expertise in a core vertical such as FSI Retail Manufacturing etc.
Required Skills :
Basic Qualification :
Additional Skills :
This is a high PRIORITY requisition. This is a PROACTIVE requisition
Background Check : No
Drug Screen : No
JOB DESCRIPTIONAI/ML ARCHITECTBe a technical expert on all aspects of Snowflake in relation to the AI/ML workload.Provide customers with best practices and advise as it relates to Data Science workloads on SnowflakeBuild and deploy ML pipelines using Snowflake features and/or Snowflake ecosystem par...
JOB DESCRIPTIONAI/ML ARCHITECT
- Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
- Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake
- Build and deploy ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements.
- Work hands-on where needed using SQL Python to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the Data Science workload.
- Follow best practices including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
- Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space and how to position Snowflake in relation to them
- Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
- Provide guidance on how to resolve customer-specific technical challenges.
- Support other members of the Professional Services team develop their expertise.
- Collaborate with Product Management Engineering and Marketing to continuously improve Snowflakes products and marketing.
- GenAI - Cortex Search / RAG
REQUIREMENTS
- University degree in data science computer science engineering mathematics or related fields or equivalent experience.
- 12-14 years experience working with customers in a pre-sales or post-sales technical role.
- Outstanding skills presenting to both technical and executive audiences whether impromptu on a whiteboard or using presentations and demos.
- Thorough understanding of the complete Data Science life-cycle including feature engineering model development model deployment and model management.
- Strong understanding of MLOps coupled with technologies and methodologies for deploying and monitoring models.
- Experience and understanding of at least one public cloud platform (AWS Azure or GCP).
- Experience with at least one Data Science tool such as AWS Sagemaker AzureML Dataiku Datarobot H2O and Jupyter Notebooks.
- Hands-on scripting experience with SQL and at least one of the following; Python Java or Scala.
- Experience with libraries such as Pandas PyTorch TensorFlow SciKit-Learn or similar.
BONUS POINTS FOR HAVING :
- Experience with GenerativeAI LLMs and Vector Databases.
- Experience with Databricks/Apache Spark.
- Experience implementing data pipelines using ETL tools.
- Experience working in a Data Science role.
- Proven success at enterprise software.
- Vertical expertise in a core vertical such as FSI Retail Manufacturing etc.
Required Skills :
Basic Qualification :
Additional Skills :
This is a high PRIORITY requisition. This is a PROACTIVE requisition
Background Check : No
Drug Screen : No
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