YOU WILL:

• Run training sessions, workshops, webinars to help Partners become proficient in Snowflake.

• Help Solution Providers/Practice Leads with technical strategies that enable them to sell their offerings on Snowflake.

• Keep Partners up to date on key Snowflake product updates and future roadmaps to help them represent Snowflake to their clients about latest technology solutions and benefits.

• Run technical enablement programs to provide best practices and solution design workshops to help Partners create effective solutions.

• Have a Forward Strategic thinking - quickly grasp the essence of new concepts and business value messaging, sharing customer success stories and case studies to showcase the impact of Snowflake.

• Have a strong understanding of how Partners make revenue through the Industry priorities & complexities they face and influence where Snowflake products can have the most impact for their product services.

• Have conversations with other technologists, providing presentations at the C-level.

• ML Engineering and Development skills - 

  • Work with large-scale datasets, preprocess them, and create appropriate data representations

  • Select relevant features and ensure data quality for training and evaluation

  • Implement and fine-tune neural network architectures, including transformer-based models

  • Optimize model performance, scalability, and efficiency

  • Conduct experiments to evaluate model performance, robustness, and generalization

  • Explore novel techniques and approaches to enhance model capabilities.

  • Stay up-to-date with the latest advancements in machine learning, deep learning, and AI research

OUR IDEAL CANDIDATE WILL:

• Provide technical, product and deep architectural expertise on the latest product capabilities with our Partner Solution Architect community.

• Stay current with the latest Snowflake product updates and best practices

• Have a total of 10+ years of relevant experience

• Have in-depth knowledge and hands-on experience in Data Science, Generative AI and Engineering

• Background in machine learning, deep learning, and natural language processing.

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade quality products

• Experience with distributed systems design and implementation

• Proficiency in Agile development practices and Continuous Integration/Continuous Deployment (CI/CD), including DataOps and MLops

• Experience with transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion)

• Good understanding of statistics, linear algebra, and probability theory

• Familiarity with cloud platforms (e.g., Azure, AWS) and distributed computing

• Excellent problem-solving skills and the ability to work independently and collaboratively

• Experience using Big Data or Cloud integration technologies such as Azure Data Factory, AWS Glue, AWS Lambda, etc

• Experience with databases