Technical Architect AI/ML

Reposted Yesterday
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Mumbai, Maharashtra, IND
In-Office
Expert/Leader
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Database • Analytics
Let's build a world where data and AI turn possibilities into reality.
The Role
Design and deploy AI/ML solutions on Snowflake, build ML pipelines and POCs using SQL/Python/APIs, advise customers and systems integrators, enable teams via best practices, collaborate with Product/Engineering, and travel to customer sites (~25%).
Summary Generated by Built In

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 AI/ML Workload Services team to create exciting new offerings and capabilities for our customers! This team within the Services Delivery 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 TECHNICAL 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, and APIs to build POCs that demonstrate implementation techniques and best practices on Snowflake technology for GenAI and ML workloads

  • 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 Services Delivery team develop their expertise

  • Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing

  • Ability and flexibility to travel to work with customers on-site 25% of the time

OUR IDEAL TECHNICAL 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 Sagemaker, AzureML, Vertex, Dataiku, DataRobot, H2O, and Jupyter Notebooks

  • Experience with Large Language Models, Retrieval and Agentic frameworks

  • Hands-on scripting experience with SQL and at least one of the following; Python, R, 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 Generative AI, LLMs and Vector Databases.

  • Experience with Databricks/Apache Spark, including PySpark

  • 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?

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

Skills Required

  • Strong background in data science and cloud architecture
  • Minimum 10 years experience in pre-sales or post-sales technical customer-facing roles
  • Presenting to technical and executive audiences with demos and whiteboard sessions
  • Thorough understanding of the complete Data Science lifecycle (feature engineering, model development, deployment, management)
  • Strong understanding of MLOps and related deployment/monitoring technologies and methodologies
  • Experience with at least one public cloud platform (AWS, Azure, or GCP)
  • Experience with at least one data science platform/tool (SageMaker, AzureML, Vertex, Dataiku, DataRobot, H2O, Jupyter Notebooks)
  • Experience with Large Language Models, retrieval and agentic frameworks
  • Hands-on scripting with SQL and at least one of: Python, R, Java, or Scala
  • Experience with libraries such as Pandas, PyTorch, TensorFlow, Scikit-Learn or similar
  • University degree in computer science, engineering, mathematics or related, or equivalent experience
  • Ability and flexibility to travel to customer sites ~25% of the time
  • Experience with Generative AI, LLMs and Vector Databases
  • Experience with Databricks/Apache Spark including PySpark
  • Experience implementing data pipelines using ETL tools
  • Prior experience working in a Data Science role
  • Proven success at enterprise software and vertical expertise (FSI, Retail, Manufacturing, etc.)

Snowflake Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snowflake and has not been reviewed or approved by Snowflake.

  • Fair & Transparent Compensation Pay is considered competitive across many roles, and the company highlights structured practices aimed at pay equity. Total compensation is often described as strong at senior levels when equity and bonuses are included.
  • Equity Value & Accessibility Equity grants and an ESPP are standard, making ownership accessible and a meaningful part of total rewards. New-hire RSUs and ongoing equity alongside bonus/commission programs are emphasized.
  • Healthcare Strength Comprehensive medical coverage is offered with programs like Lyra providing up to 25 no-cost therapy/coaching sessions, alongside HSA-eligible plans. Wellness resources and additional clinical programs (such as Omada for certain conditions) broaden the scope of support.

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The Company
HQ: Bozeman, MT
9,023 Employees
Year Founded: 2012

What We Do

Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.

Why Work With Us

Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.

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