What are the responsibilities and job description for the Snowflake AI/ML Senior Solutions Architect position at NimbusAITech LLC?
Job Details
Job Title: Snowflake AI/ML Senior Solutions Architect
Type: Contract
Location: New York, NY (Onsite required talent preferred to be reside locally)
About the Role
Seeking a seasoned Snowflake AI/ML Solutions Architect to drive technical leadership for AI/ML workloads in enterprise environments. The role focuses on designing, implementing, and optimizing advanced data science solutions leveraging Snowflake s platform and ecosystem. Ideal candidates bring deep hands-on expertise, a strong customer orientation, and fluency in the modern AI/ML stack.
Responsibilities
- Serve as the technical authority for Snowflake s AI/ML capabilities, guiding customers and partners on all aspects of data science workloads.
- Advise on best practices for building and deploying scalable ML pipelines using Snowflake features and partner tools.
- Develop proof-of-concept solutions and demos using SQL and Python to demonstrate end-to-end data science life cycles within Snowflake.
- Ensure effective knowledge transfer, enabling customers to independently scale and manage data science/ML solutions.
- Maintain up-to-date understanding of key technologies and vendors in the AI/ML ecosystem to competitively position Snowflake.
- Collaborate closely with System Integrators and internal teams to enable successful deployment and integration in client environments.
- Troubleshoot and resolve customer-specific technical challenges related to AI/ML workloads.
- Mentor Professional Services colleagues, elevating team expertise.
- Coordinate with Product Management, Engineering, and Marketing to help shape Snowflake s evolving capabilities.
- Execute replatforming initiatives, such as migrating chat bots to Snowflake Cortex Analyst and integrating unstructured data search.
- Support the integration and enhancement of existing predictive ML models into new Snowflake-based solutions.
Required Qualifications
- Bachelor s or advanced degree in Data Science, Computer Science, Engineering, Mathematics or a related discipline, or equivalent experience.
- 12 14 years experience in technical roles supporting customers pre-sales or post-sales.
- Exceptional communication ability with both technical and executive audiences.
- Strong grasp of the full data science lifecycle, including model development, deployment, management, and monitoring.
- Proficient in MLOps, with experience in deploying and monitoring AI models.
- Deep familiarity with at least one public cloud (AWS, Azure, or Google Cloud Platform).
- Hands-on experience with data science platforms (e.g., AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, Jupyter Notebooks).
- Solid scripting skills in SQL and at least one language: Python, Java, or Scala.
- Expertise with data science libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn, or similar.
Preferred Qualifications
- Experience with Generative AI, LLMs, and Vector Databases.
- Familiarity with Databricks and Apache Spark.
- Background in building data pipelines with ETL tools.
- Direct experience in Data Science functions.
- Success supporting enterprise software solutions.
- Vertical domain expertise (e.g., Financial Services, Retail, Manufacturing).
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Salary : $80 - $90
