Staff Machine Learning Engineer (Applied ML)

About EarnIn

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks.

We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.

POSITION SUMMARY

Machine learning is integral to every financial service we provide. As we embark on a transformative phase, EarnIn is making significant investments to innovate and set new standards in ML applications within fintech. We are seeking skilled engineers to create groundbreaking solutions with large language models, generative AI, and advanced machine learning algorithms, generating substantial business and social impact.

Machine learning is the enabler for every financial service EarnIn provides its community members. We are going through transformative investments in machine learning. We aim to lead the innovation and operational excellence in machine learning for the fintech industry. We seek experienced engineers to create first-of-a-kind success stories through large language models, generative AI, and state-of-the-art machine learning algorithms and realize outsize business and social impact.

The Mountain View base salary range for this full-time position is $272,700 - $333,300 plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Mountain View and will require in-office work 2-3 days a week.

WHAT YOU'LL DO

• Design, develop, A / B test, and deploy risk models while collaborating with data scientists to drive data-driven decisions.
• Enhance credit and fraud models by incorporating innovative features on a quarterly basis and leveraging the latest industry research.
• Monitor feature and model health, and communicate changes in model decisions.
• Explore and integrate advanced technologies, including deep learning in the risk domain.
• Lead by example to foster operational excellence and transformative change.
• Expand responsibilities as new products emerge.

WHAT WE'RE LOOKING FOR

#LI-Hybrid

At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant.

EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.