Senior AI/ML Architect, Applied Field Engineering at Snowflake

Menlo Park, California, United States

Snowflake Logo
$165,000 – $216,600Compensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Technology, Data CloudIndustries

Requirements

  • 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud
  • Familiarity and associated knowledge of generative AI techniques like RAG, few shot learning, prompt engineering, or fine-tuning that are used to operationalize enterprise AI use cases like interactive chat applications or text processing
  • Deep knowledge of Python and common ML packages (such as LangChain, pandas, sklearn, and PyTorch) as well as data engineering tools and technologies like dbt, Airflow, and Spark
  • Strong presentation skills to both technical and executive audiences, whether whiteboarding sessions or formal readouts and demos
  • Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred

Responsibilities

  • Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas
  • Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases
  • Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback
  • Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos
  • Influence, tailor and maintain Sales Engineering AI and ML selling assets, including customer presentations, demonstrations, and customer stories

Skills

Key technologies and capabilities for this role

AIMLGenerative AIRAGFew Shot LearningPrompt EngineeringFine-tuningSnowflakeCloudMachine Learning

Questions & Answers

Common questions about this position

What is the salary range for the Senior AI/ML Architect role?

The salary range is $165K - $216.6K.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What skills are required for this Senior AI/ML Architect position?

Candidates need 5+ years of experience building and deploying ML and generative AI solutions in the cloud, deep knowledge of Python and ML packages like LangChain, pandas, sklearn, and PyTorch, plus data engineering tools like dbt, Airflow, and Spark, and strong presentation skills.

What is the company culture like at Snowflake?

Snowflake has a culture focused on impact, innovation, and collaboration, empowering enterprises and people to build big, move fast, and advance technology and careers.

What makes a strong candidate for this role?

A strong candidate has 5+ years in ML and generative AI, expertise in Python/ML tools and data engineering, strong presentation skills, and bonus for LLM tools, cloud platforms, and Snowflake experience.

Snowflake

Data management and analytics platform

About Snowflake

Snowflake provides a platform called the AI Data Cloud that helps organizations manage and analyze their data. This platform allows users to store and process large amounts of data efficiently, offering services like data warehousing, data lakes, data engineering, data science, and data sharing. Snowflake's system works by uniting data from different sources, enabling secure sharing and performing various types of analytics. What sets Snowflake apart from its competitors is its ability to operate seamlessly across multiple public clouds, allowing users to access their data from anywhere. The company's goal is to help businesses leverage their data for better decision-making by providing a flexible subscription-based service that scales according to their needs.

Bellevue, WashingtonHeadquarters
2012Year Founded
$1,341.3MTotal Funding
IPOCompany Stage
Data & Analytics, Enterprise Software, AI & Machine LearningIndustries
5,001-10,000Employees

Benefits

We've got your back - We offer comprehensive health insurance plans, health savings accounts, robust retirement plans, and generous life and disability insurance.
A Balanced Lifestyle - All Snowflakes have access to our weekly online lunch and learns, virtual workout classes, and ergonomic work-from-home equipment. We offer on-demand mental health and wellness programs to support our employees and their families.
Your People Matter - Help offset the cost of growing your family with our fertility benefits and family planning resources. Count on our generous time-off and various leave plans for you to rest, refuel, and sustain a great work-life balance.
Global Snowflake Team - No matter where you are in the world, we will get you connected and supported with a work-from-home setup.
Treat Yourself - Personalize your Snowflake benefits by tapping into our employee discounts and pre-tax selections.
Invest In Your Future - Eligible employees enjoy new hire equity, Employee Stock Purchase Plan (ESPP), and a quarterly bonus or commission program.

Risks

Integration challenges from Datavolo acquisition may disrupt operations and customer service.
Increased competition from Mistral AI could challenge Snowflake's market position.
Convertible senior notes pricing may increase financial pressure if market conditions worsen.

Differentiation

Snowflake offers a unified platform for diverse data workloads, unlike traditional solutions.
The AI Data Cloud enables near-unlimited scale and performance for data mobilization.
Snowflake's seamless multi-cloud experience ensures efficient data operations across locations.

Upsides

Acquisition of Datavolo enhances Snowflake's open data integration capabilities.
Investment in Metaplane boosts AI-driven data quality solutions for Snowflake users.
Snowflake Ventures' investment in Hex expands accessibility of data tools to non-technical users.

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