FreshRemote.Work

Machine Learning Engineer

San Francisco, Seattle, Portland, New York, or Remote

About Found

The self-employed workforce is a rapidly growing, resilient, and colorful 60 million Americans. But self-employment comes with its own set of challenges: navigating taxes, accounting, bookkeeping, and business banking are just a few. That’s where we come in.

Found is building tools that give self-employed people the security and peace of mind that has historically only been possible at big corporations. We’re a business bank account that automates taxes and expense tracking because we believe small business owners should spend more time doing what they love and less time on their business finances.

We’re looking for kind, resourceful, and passionate people to join us in building the safety net for self-employment.

About this role: 

Thanks for your interest in Found!  Our Data team is a full stack data organization of highly skilled analysts, data engineers, and MLEs. We’re responsible for everything from researching, training, and deploying ML models to detect and stop fraud in real time, to using data to inform the direction that our product teams should take / what to build next.

We’re a small but experienced team that has worked on diverse and complex problems at companies like Uber, Netflix, and Spotify. We’re excited to bring on another member to our team to enhance our Data Science and ML capabilities. You’ll start by partnering with our risk team to develop models to better identify risky activity, underwrite users for things like higher account limits or access to check deposits, and improve our understanding of user quality through identifying signals of ‘real’ vs. fraudulent businesses. We’re looking for someone who’s curious, proactive, and who is excited to dive in and immediately play a critical role impacting company-level strategic priorities. 

Some recent team accomplishments include: 

  • Researching, training, and deploying an XGBoost model that predicts a user’s LTV to better shape our ad targeting and user acquisition strategy. 

  • Deploying a new feature store that improved time to train and deploy models by ~50%. 

  • Optimizing our batch and streaming jobs to improve reporting latencies from a matter of days to a matter of hours. 

  • Training and building several models that monitor financial transactions in real time to make decisions on whether or not they should be allowed through or not.  

  • Customizing onboarding flows based on user behavior and expected value to cut onboarding CAC by ⅓ and optimize upsells/CTAs.

Day to day, you will:

  • Design, develop, and deploy machine learning models to identify fraudulent activity, unlock things like higher limits for good users, and decision on transactions.

  • Collaborate with cross-functional teams, including product and engineering, to identify new opportunities to solve business problems through data science & ML.

  • Communicate complex machine learning concepts and results to both technical and non-technical stakeholders.

  • Research novel techniques and best practices to parse large, diverse data sets.

  • Contribute to the development of best practices, standards, and frameworks for machine learning at Found.

  • Provide mentorship and guidance to help grow and develop the skills of the broader data team, fostering a culture of continuous learning and excellence.

To thrive in this role, you have:

  • 6+ years in Data Science or Machine Learning

  • Expertise with Python/R and SQL. 

  • Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.

  • Proven track record of developing and deploying successful machine learning models in a production environment.

You may also have:

  • Previous experience working in the fintech space. 

  • Experience in building ML-based lead scoring models.

  • Previous startup experience.

  • Experience with bookkeeping or taxes and how it relates to self-employment.

Compensation at Found 

The anticipated salary range for this role is $180,000 - $209,000. The salary range listed represents the low and high end of the anticipated salary range for this position across all US locations. Within the range, individual pay is determined by several factors including job-related skills, experience, and relevant education or training. Our competitive base salary is just a piece of Found’s total compensation package. Found offers a generous benefits package to all employees see our list below or check out found.com/careers to learn more!

#LI-DNI

About You

Found is built by a team that comes from a variety of backgrounds and experiences, and we firmly believe that diversity, equity, and inclusion are crucial to our success. As we grow, we’re searching for passionate and motivated team members who are excited to bring their skill set to the team and are ready to learn from others.

If you are looking for a role where you will have the opportunity to make a meaningful contribution and great impact, we would love to hear from you!

Perks & Benefits of Found
  • 401K, FSA, and Commuter Benefits: We offer all employees access to tax-efficient benefit options alongside competitive base compensation.

  • Paid parental leave: Found supports employees through all stages of life, which is why new parents employed by Found qualify for 16 weeks of flexible parental leave.

  • Health benefits: Comprehensive medical, dental, and vision benefits and are always 100% covered for employees, 75% covered for dependents.

  • Work anywhere: We have Found offices in SF, Seattle, and NYC. For team members who work outside those cities, Found also supports fully remote working.

  • Meaningful equity: Everyone on our team should feel and act like an owner, which is why Found offers industry-competitive equity to all of our employees.

  • Flexible vacation policy: Vacations, appointments, mental health days- take the time you need, whenever you need to with our flexible time-off policy

To learn more about our benefits or the team please go to found.com/careers.

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