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.
The Palo Alto base salary range for this full-time position is $232,200 - $283,800 plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Palo Alto and will require in-office work 2 days a week.
WHAT YOU'LL DO: Design, develop, A/B test, and deploy machine learning models that drive EarnIn's products. Train, fine-tune, evaluate, and operationalize large language models (LLMs) and AI agents, delivering radical efficiency gains to our core processes. Continuously improve model performance by leveraging the latest research and open-source tools. Champion data-driven decision-making and maintain scientific rigor in the deployment of ML solutions. Collaborate closely with ML platform engineers to optimize tools and processes for stability and reproducibility. Explore and integrate cutting-edge technologies to enhance EarnIn's ML capabilities. Lead by example, fostering an environment of operational excellence and driving transformative change. WHAT WE'RE LOOKING FOR Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 4+ years of experience in machine learning with strong software engineering skills. Proficiency in a broad range of ML techniques, including LLMs, deep learning, sequence models, and tree-based models. Advanced programming skills in Python and experience with ML frameworks such as TensorFlow or PyTorch. Hands-on experience with cloud-based ML platforms (e.g., AWS Sagemaker, Databricks, GCP Vertex AI). Hands-on experience with modern LLM stack: foundations models and APIs such as Open AI and Antropic; LLM guardrails, framework such as LangGraph, LangChain; ML flow. Strong communication and collaboration skills. Passion for continuous learning and staying updated on 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.
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