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Careers at Ramp
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Staff Machine Learning Engineer

$185,000 - $315,000/year
12 Mar 2025
New York, NY, USA
Verified by Turrior

Content + Source + Freshness • 12 Dec 2025 • 95% confidence

90 / 100

Offer value

Exceptional value aligned with Ramp's strategic focus on machine learning, offering competitive compensation and significant growth potential.

  • Strategic role in machine learning and identity security
  • Top compensation reflecting the industry's demand for specialists
  • Opportunity to make a significant impact on operations
Pros
  • Leading role in the future of identity-related machine learning
  • High salary range that reflects the demand for expertise
  • Opportunity to influence critical security initiatives
Cons
  • Heavy responsibilities can create pressure
  • Constantly evolving field requires ongoing learning
  • Requires deep technical knowledge and experience

Who it's for

Senior • Hybrid with flexibility in work location

Good fit
  • Senior machine learning engineers
  • Professionals passionate about identity security
  • Individuals eager to innovate in the field
Not recommended for
  • Candidates with limited experience in machine learning
  • Those uninterested in focusing on security applications
  • Less experienced professionals seeking entry-level roles

Motivation fit

Desire to tackle identity-related challenges with technologyInterest in making a substantial impact via ML modelsAspirations in advanced analytics and data strategy

Key skills

Machine learning algorithms and techniquesStatistical analysis and data architectureProficiency in Python and SQLExperience in deploying ML models
Score: 90/100 AI verified analysis

About the job

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 25,000 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 Notice

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