Lead Machine Learning Scientist, Snowflake

$114-166.7k

+ Bonus and equity

Python
Senior and Expert level
San Francisco Bay Area

3-5 days a week in office (Menlo Park, CA)

Snowflake

AI Data Cloud for data sharing and app building

Job no longer available

Snowflake

AI Data Cloud for data sharing and app building

1001+ employees

B2BArtificial IntelligenceData storageEnterpriseAnalyticsMachine LearningSaaSData AnalysisCloud ComputingData Sharing

Job no longer available

$114-166.7k

+ Bonus and equity

Python
Senior and Expert level
San Francisco Bay Area

3-5 days a week in office (Menlo Park, CA)

1001+ employees

B2BArtificial IntelligenceData storageEnterpriseAnalyticsMachine LearningSaaSData AnalysisCloud ComputingData Sharing

Company mission

On a mission to mobilize the world's data.

Role

Who you are

  • High levels of curiosity, eager enthusiasm & demonstrable experience working on open-ended problems. Exceptional problem solving skills with the ability to think strategically. Demonstrable experience and interest in problem formulation based on relatively abstract information
  • High levels of adaptability, to respond to fast-evolving project scope, adjusting strategies & plans while delivering value; comfortable being scrappy
  • Experience applying AI, ML & statistical modeling on large datasets; pre-processing, data quality, feature engineering; the whole nine-yards
  • Deep understanding of the basic classes of ML algorithms, statistics & linear algebra; with a keen interest in the underlying theory & assumptions
  • Experience building AI & LLM based applications in a business environment; up to date with advancements in the Gen-AI space, in an applied sense with techniques such as RAG, in-context learning, search, agentic workflows etc
  • Solid understanding of NLP, embedding methods, foundational models and model fine-tuning; with experience in developing conversational & agentic AI
  • Experience writing production-quality, scalable code using Python. Strong with the software development lifecycle and its best practices
  • Experience managing AI/ML project lifecycles; with a point-of-view for designing and developing end-to-end turn key ML solutions, enablement & adoption baked into the solution. Also experience iterating on ideas and deliverables
  • Strong stakeholder management skills; with the ability to articulate results and complex concepts to all audiences. Also the ability to work with leadership
  • Demonstrate keen senses of ownership, collaboration and mentorship
  • Proven experience leading and mentoring AI/ML teams; demonstrate leadership, with the ability to inspire the team & lead a project to completion

What the job involves

  • We’re looking for a Lead ML Scientist for Snowflake's Corporate Machine Learning team. In this role, you will apply AI & ML to a variety of domain specific problems across Snowflake’s business data
  • This is a generalist role and will provide an opportunity to work on a wide breadth of problems, applying a good mix of models & methods to structured & unstructured data, driving large-scale projects from idea to completion
  • Lead projects; Conceptualize, design and lead the execution of large AI & ML projects, aligning with the business goals, delivering measurable value & impact
  • Engage with stakeholders; lead the conversations with technical & non-technical stakeholders; identify areas where one can apply AI & ML; facilitating discussions around key drivers for decision making & operational efficiencies
  • Provide technical & thought leadership; designing and implementing advanced machine learning techniques, focusing on robust & scalable solutions. Participate in all stages of development, ideation to production
  • Provide mentorship; to junior ML & Data Scientists, around problem formulation, technical design, algorithm choices & code quality
  • Develop hands-on; analyze large amounts of data, manage data quality, design & develop complex ML models (and the ensuing ML solutions) including ML pipelines, deploy & manage production-grade applications end-to-end, and tell the story in a compelling manner
  • Partner with customers; showcase internal solutions to customers, help them envision solutions stringing Snowflake platform capabilities together, partner with internal teams that enable customer solutions
  • Set technical direction and strategy; by defining the roadmap and aligning it with business goals. Also guiding the team in prioritizing projects for impact
  • Oversee team execution and deliverables; to ensure high-quality execution by managing team workflows, reviewing deliverables and optimizing the ensuing processes

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Insights

Top investors

37% employee growth in 12 months

Company

Company benefits

  • Comprehensive health insurance plans
  • Health savings accounts
  • Robust retirement plans
  • Life and disability insurance
  • Weekly online lunch and learns
  • Virtual workout classes
  • Ergonomic work-from-home equipment
  • On-demand mental health and wellness programs
  • Fertility benefits and family planning resources
  • Generous time-off and various leave plans
  • Onsite and Remote Work
  • Employee discounts and pre-tax selections
  • New hire equity + Employee Stock Purchase Plan (ESPP)
  • Quarterly bonus or commission program

Funding (last 2 of 9 rounds)

Feb 2020

$479m

LATE VC

Oct 2018

$450m

LATE VC

Total funding: $1.4bn

Our take

Developed as a fresh alternative to the archaic systems of data governance and information silos, Snowflake is a frictionless cloud data platform that removes the barriers preventing organizations of all sizes from unleashing the true value of their data.

The company equips organizations with a single, integrated platform that offers the only data warehouse built for the cloud; instant, secure and governed access to their entire network of data; and a core architecture to enable many types of data workloads, including a single platform for developing modern data applications.

Major competitors include Azure, SQL and AWS, and Snowflake has managed to keep ahead of the competition, cementing itself as a global force. Across its 1300+ partners, the company's cloud manages over 250PB of data (with more than 515 million data workloads running every day). Its continued focus on product R&D and partnership expansion have Snowflake well-positioned to manage itself amidst the competition.

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Freddie

Company Specialist at Welcome to the Jungle