Staff Machine Learning Engineer, Ramp
$185-315k
Listed salary applies to SF and NYC only. Offers Equity
More information about location
Corporate cards and finance automation
Open for applications
Corporate cards and finance automation
501-1000 employees
Open for applications
$185-315k
Listed salary applies to SF and NYC only. Offers Equity
More information about location
501-1000 employees
Company mission
To help finance teams build healthier businesses.
Role
Who you are
- 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
Desirable
- 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)
What the job involves
- 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
- 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
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Insights
77% employee growth in 12 months
Company
Company benefits
- Comprehensive medical, dental, and vision insurance
- One Medical Membership
- 401(k) including an employer match
- Unlimited PTO
- Parental leave
- Monthly wellness stipend
- WFH stipend
- Relocation support to move to NYC
- Pet Insurance
Funding (last 2 of 8 rounds)
Apr 2024
$150m
SERIES D
Aug 2023
$300m
SERIES D
Total funding: $1.1bn
Our take
Ramp provides companies with a dual offering of corporate cards and a spending management dashboard. The dashboard allows companies to oversee their costs, automate manual accounting practices, reimburse out-of-pocket spending, and earn cashback on financial outlays.
Founded in 2019 and coming out of stealth in 2020, the company has already reached a valuation of a whopping $8.1 billion in early 2022. Its clients include several big-name companies including fast-growth health tech startup Ro, Planned Parenthood, and Truebill. 90% of its customers have made the switch from legacy players such as Expensify and Concur, showing that Ramp provides real customer value.
The team that built Ramp is the same one that launched the automated price tracking company Paribus before selling it to Capital One. It is now focused on scoping out more M&A opportunities and boosting its headcount to support investing in its software and going into new verticals.
Freddie
Company Specialist at Welcome to the Jungle