Snowflake의 Professional Services 팀에서 AI/ML 기술 아키텍트를 채용합니다. 고객의 데이터 과학 워크로드를 Snowflake 환경에서 성공적으로 구현하도록 지원하며, 데이터 과학 라이프사이클 및 MLOps에 대한 깊은 이해와 6년 이상의 기술 컨설팅 경력이 필수입니다. 클라우드 환경에서의 데이터 파이프라인 설계 및 구축 역량을 갖춘 분을 찾습니다.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
We are looking for people who have a strong background in data science and cloud architecture to join our Professional Services team to help create exciting new offerings and capabilities for our customers! This team will be working with customers using Snowflake to expand their use of the Snowflake Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be more strategic, advising our clients on best practices and advice to implement Data Science workloads on Snowflake. You will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators, while maintaining oversight and direction to ensure successful outcomes
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, deploy and 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 Snowflake’s products and marketing
University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience
Minimum 6 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
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
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
