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- Tasks: Design and implement AI/ML solutions using Snowflake's Data Cloud.
- Company: Join Snowflake, a fast-growing leader in cloud data solutions.
- Benefits: Enjoy flexible work options and a culture of innovation.
- Why this job: Be part of a team that shapes the future of AI and data science.
- Qualifications: 10+ years in technical roles with strong data science and cloud skills.
- Other info: Opportunity to collaborate with top professionals and enhance your expertise.
The predicted salary is between 43200 - 72000 £ per year.
Build the future of the AI Data Cloud. Join the Snowflake team.
We are looking for people who have a strong background in data science and cloud architecture to join our AI/ML Workload Services team to create exciting new offerings and capabilities for our customers! This team within the Professional Services group will be working with customers using Snowflake to expand their use of the 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 highly technical and hands-on, where you will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators.
AS A SOLUTIONS ARCHITECT - AI/ML AT SNOWFLAKE, YOU WILL:
- Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload
- 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, Java and/or Scala 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
OUR IDEAL SOLUTION ARCHITECT - AI/ML WILL HAVE:
- Minimum 10 years experience working with customers in a pre-sales or post-sales technical role
- 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
- University degree in computer science, engineering, mathematics or related fields, or equivalent experience
BONUS POINTS FOR HAVING:
- 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
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?
Solutions Architect AI/ML employer: Snowflake
Contact Detail:
Snowflake Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Solutions Architect AI/ML
✨Tip Number 1
Familiarise yourself with Snowflake's features and capabilities, especially those related to AI/ML workloads. Understanding how to leverage these tools will not only help you in interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Network with current employees or professionals in the AI/ML space who have experience with Snowflake. Engaging in conversations can provide insights into the company culture and expectations, which can be invaluable during the interview process.
✨Tip Number 3
Prepare to discuss specific projects where you've implemented data science solutions or cloud architectures. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your hands-on experience.
✨Tip Number 4
Stay updated on the latest trends and technologies in AI/ML and cloud computing. Being knowledgeable about competitive technologies and how they relate to Snowflake will allow you to position yourself as a well-informed candidate.
We think you need these skills to ace Solutions Architect AI/ML
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Solutions Architect AI/ML position at Snowflake. Familiarise yourself with the key technologies mentioned in the job description, such as SQL, Python, and cloud platforms.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job description. Emphasise your background in data science, cloud architecture, and any hands-on experience with AI/ML technologies.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI/ML and your understanding of Snowflake's offerings. Use specific examples from your past experiences to demonstrate how you can contribute to the team and help customers succeed.
Highlight Technical Expertise: In your application, be sure to detail your technical expertise, especially in areas like MLOps, data pipelines, and the Data Science life-cycle. Mention any relevant tools or libraries you have worked with, as this will show your capability to handle the role's technical demands.
How to prepare for a job interview at Snowflake
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with SQL, Python, Java, or Scala. Highlight specific projects where you've built ML pipelines or POCs using Snowflake or similar technologies, as this will demonstrate your capability to handle the technical demands of the role.
✨Understand the Data Science Lifecycle
Familiarise yourself with the complete Data Science lifecycle, including feature engineering, model development, deployment, and management. Be ready to discuss how you have applied these concepts in previous roles, as this knowledge is crucial for the Solutions Architect position.
✨Prepare for Customer Interaction Scenarios
Since the role involves working closely with customers, practice articulating complex technical concepts in a way that is accessible to both technical and executive audiences. Consider preparing a few scenarios where you've successfully communicated solutions to clients.
✨Research Snowflake and Competitors
Gain a deep understanding of Snowflake's features and how they compare to competitors in the AI/ML space. Being able to position Snowflake effectively against other technologies will show your strategic thinking and readiness to contribute to the team.
