Senior Applied Machine Learning Engineer
About The Position
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. This role will focus on developing groundbreaking foundational ML Models and solutions generating substantial business and social impact. The 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 requiring 2 days a week in our Mountain View office
Requirements
- Bachelor’s/Master’s in Computer Science, Engineering, or equivalent industry experience.
- 4+ years of machine learning experience with strong software engineering skills.
- Proficiency in ML techniques (LLMs, deep learning, sequence, and tree-based models)
- Advanced Python programming, SQL, and data manipulation skills.
- Experience with ML frameworks (TensorFlow, PyTorch) and cloud platforms (AWS Sagemaker, Databricks, GCP Vertex AI).
- Excellent communication and collaboration abilities.
- A passion for continuous learning and personal growth in a dynamic work environment
Nice To Haves
- Experience with Risk modeling for financial use cases is a bonus
Responsibilities
- Design, develop, A/B test, and deploy models while collaborating with data scientists to drive data-driven decisions.
- Enhance models by incorporating innovative features every quarter 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 and LLMs, in the risk domain.
- Lead by example to foster operational excellence and transformative change.
- Expand responsibilities as new products emerge.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
251-500 employees
