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. Since our founding, our app has been downloaded over 13M times and we have provided access to over $15 billion in earnings.

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

The US base salary range for this full-time position is $223,700 - $333,300 + equity + benefits. Our salary ranges are determined by role, level, and location. This is a remote role with a preference for hybrid in our Palo Alto HQ. 

WHAT YOU’LL DO

• Design, build, A/B test and maintain machine learning models to power EarnIn products
• Continuously optimize the quality of our machine learning models through state-of-the-art machine learning techniques such as deep learning, sequence models, large language models, and recently published work
• Champion scientific rigor in data-driven decision-making
• Work closely with ML platform engineers to optimize ML tooling and processes to ensure stability and reproducibility
• Contribute to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities
• Provide technical guidance and mentorship to junior team members
• Set examples of outstanding operational excellence. Be the catalyst of step-jump changes

WHAT WE’RE LOOKING FOR

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 7+ years of industry machine learning experience and excellent software engineering skills
• Expertise in the breadth of machine learning modeling techniques such as tree-based models, deep learning techniques, sequence models, and large language models
• Strong programming skills in Python, and familiarity with ML frameworks such as TensorFlow or PyTorch
• Experience with ML cloud platforms such as AWS Sagemaker, Databricks, or GCP Vertex AI
• Strong communication and collaboration skills
• Passion for learning and staying updated with the latest machine-learning industry trends

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.