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Machine Learning Engineer

New York, NY (HQ) · Remote (US) · New York City, NY, USA

Open 5 months, first seen by us 155 days ago
Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Data — team source

What you’ll work on

Full posting

We’re seeking someone to lead the future of fraud machine learning at Ramp.

  • Find fraud, platform abuse, and identity theft patterns in large datasets using statistics and ML

  • Prototype and ship ML models and rules-based systems against fraud

  • Combine first and third party data to add context to each decision

  • Shape ML team processes, tools, and systems for scalable decisions

From the employer’s posting
We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis.
Employ statistical and machine learning techniques on large datasets to discover patterns of fraud, platform abuse, and identity theft
Prototype and productionize machine learning models and rules-based systems to protect Ramp and its users from fraud
Partner closely with Fraud Engineering and Data Platform teams to augment and leverage data across first and third party sources
influencing processes, tools, and systems that will allow us to make better decisions in a scalable way

What you’ll bring

All qualifications

Core experience

  • Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields
  • Experience at a high-growth startup
  • Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and backend engineering
  • Experience with the modern data stack ( Snowflake / Hex / dbt / RisingWave / etc )
  • Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
  • Experience developing LLM-backed systems or tools
Qualification wording
Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields
Experience at a high-growth startup
Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and backend engineering
Experience with the modern data stack ( Snowflake / Hex / dbt / RisingWave / etc )
Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
Experience developing LLM-backed systems or tools
Education & alternatives
What You Need - Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields - A minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist or Data Scientist
Nice-to-Haves - PhD in Math, Economics, Physics, Computer Science, or other quantitative fields - Context on Fraud and/or Identity Threat detection systems

About Ramp

Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends.

In the employer’s words · Read in context · Company website ↗

Apply at Ramp

Posting record

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Open 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 2, 2026155 days ago
Recorded sightings
199
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 155

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,331 similar postings that came down. Coming down is not always a hire.

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Snowflake
  • NumPy
  • pandas
  • PyTorch
  • PostgreSQL
  • scikit-learn
Where the posting names them
- 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 backend engineering - Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
- Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems - Strong knowledge of SQL (Snowflake, Postgres, etc.) - Fluency with agentic (AI) tools for software development and data analysis
- Experience at a high-growth startup - Experience with the modern data stack ( Snowflake / Hex / dbt / RisingWave / etc ) - Strong perspective on data science + ML engineering development cycle, especially in a post-AI setting

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

About Ramp

Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.

The problems are high-stakes, data-dense, and unforgiving.

We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.

The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.

If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.

About the Role

We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis.

What You’ll Do

  • Employ statistical and machine learning techniques on large datasets to discover patterns of fraud, platform abuse, and identity theft

  • Prototype and productionize machine learning models and rules-based systems to protect Ramp and its users from fraud

  • Partner closely with Fraud 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, Physics, Computer Science, or other quantitative fields

  • 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 backend engineering

  • Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems

  • Strong knowledge of SQL (Snowflake, Postgres, etc.)

  • Fluency with agentic (AI) tools for software development and data analysis

  • Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions

Nice-to-Haves

  • PhD in Math, Economics, Physics, Computer Science, or other quantitative fields

  • Context on Fraud and/or Identity Threat detection systems

  • Experience at a high-growth startup

  • Experience with the modern data stack ( Snowflake / Hex / dbt / RisingWave / etc )

  • Strong perspective on data science + ML engineering development cycle, especially in a post-AI setting

  • Experience developing LLM-backed systems or tools

Benefits available to all full-time Ramp employees (Global)

  • Flexible PTO

  • Centralized home-office equipment ordering

  • Health and wellness stipend

  • Budget for intra-office travel

  • Weekly coffee stipend

United States

  • 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents

  • One Medical annual membership

  • 401(k), including employer match on contributions made while employed by Ramp

  • Fertility HRA (up to $10,000 per year)

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay

  • Pet insurance

  • In-office perks: lunch, snacks, drinks, and more

  • Relocation expense coverage to NYC or SF (if needed)

Canada

  • Group medical, dental, and vision coverage through Sun Life

  • Life, AD&D, and disability coverage

  • Fertility drug coverage (up to $4,000 lifetime)

  • Group Retirement Plan with employer match (RRSP + DPSP)

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay

  • Employee Assistance Program and virtual care through Lumino Health

United Kingdom

  • Private medical insurance through Freedom Elite

  • Virtual GP and at-home care via eMed x Livi

  • Workplace pension through Penfold, with salary sacrifice option

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay

Referral Instructions

If you are being referred for the role, please contact that person to apply on your behalf.

 

Other notices

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

 

Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.

 

Ramp Applicant Privacy Notice

Source details

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Location & working pattern

New York City, NY, USA

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