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Staff Machine Learning Engineer

RampNew York, New York, United StatesOnsite

About Ramp


Ramp is a financial operations platform designed to save businesses time and money. Combining corporate cards with expense management, bill payments, vendor management, accounting automation, and more, Ramp's all-in-one solution frees finance teams to do the best work of their lives. More than 30,000 companies, from family-owned farms to e-commerce giants to space startups, have saved $1B and 10M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over 35 billion dollars in purchases each year.Ramp's investors include Sequoia, Founders Fund, Thrive Capital, Khosla Ventures, Greylock, Stripe, Goldman Sachs, Coatue, and Redpoint, as well as over 100 angel investors who were founders or executives of leading companies.

The Ramp team comprises talented leaders from leading financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies such as Meta, Uber, Netflix, Twitter, Dropbox, and Instacart.Ramp has been named to Fast Company's Most Innovative Companies list and LinkedIn's Top U.S. Startups for over 3 years, as well as the Forbes Cloud 100, CNBC Disruptor 50, and TIME Magazine's 100 Most Influential Companies.

About the Role


We’re seeking someone to lead the future of identity machine learning at Ramp. In this role, you will help build core machine learning, design data architectures, and set strategic roadmaps to help Ramp reduce Identity-related threats. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis. Our goal is to provide a frictionless experience for every legitimate Ramp user. 

What You’ll Do


  • Employ statistical and machine learning on large datasets to discover patterns of account takeovers and identity theft
  • Prototype and productionalize machine learning models and rules-based systems to protect user accounts
  • Partner closely with Identity Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make
  • Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way

What You Need


  • Bachelor’s degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields with a minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist or Data Scientist
  • Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and back end engineering
  • Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
  • Strong knowledge of SQL (preferably Snowflake, BigQuery)
  • Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions

Nice-to-Haves


  • Context on Fraud and/or Identity Threat detection systems
  • Experience at a high-growth startup
  • Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Census or equivalents)
  • Strong perspective on data science engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)

Compensation


  • For candidates located in NYC or SF, the pay range for this role is $185,000 - $315,000. The final compensation will depend on the level at which the candidate is hired, as we are considering candidates for multiple levels of this role.

Benefits (for U.S.-based full-time employees)


  • 100% medical, dental & vision insurance coverage for you
  • Partially covered for your dependents
  • One Medical annual membership
  • 401k (including employer match on contributions made while employed by Ramp)
  • Flexible PTO
  • Fertility HRA (up to $5,000 per year)
  • WFH stipend to support your home office needs
  • Wellness stipend
  • Parental Leave
  • Relocation support to NYC or SF
  • Pet insurance

Other notices


Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.Ramp Applicant Privacy NoticeCompensation Range: $185K - $315K

Life at Ramp

Ramp is building the world's first finance automation platform designed to save businesses time and money. Ramp offers 5-in-1 software that consolidates corporate cards, expense management, bill payments, accounting, and reporting into one simple and free solution. More than 5,000 businesses are using Ramp, from some of the fastest growing startups and unicorns like Ro, Faire, Marqeta, ClickUp, and Applied Intuition, to established businesses across the US including Bristol Hospice, Walther Farms, Douglas Elliman, and Planned Parenthood. Founded in 2019, Ramp is NYC's fastest growing startup, having achieved a unicorn valuation of $3.9 billion in just over 2 years. Ramp has raised $620 million in funding from investors including Founders Fund, Stripe, Goldman Sachs, Coatue Management, D1 Capital Partners, Redpoint Venture, Thrive Capital, Altimeter, Iconiq, Spark Capital, and the Box Group, as well as over 100 angel investors who were founders or executives of leading companies. Ramp is part of the Forbes Fintech 50, LinkedIn Top Startups of 2021, and Fast Company's Best Workplaces for Innovators program.
Thrive Here & What We Value- Fast Company's #1 Most Innovative Company in North America- LinkedIn's #1 Top Startup in the U.S.- CNBC Disruptor- TIME100 Most Influential Company- Collaborative Teamwork- Focus on Building Healthy Businesses- Strong Technical Skills- Continuous Learning and Development Opportunities- Ramp is the ultimate platform for modern finance teams.- Combining corporate cards with expense management, bill payments, vendor management, accounting automation and more

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