Staff Machine Learning Engineer

at  Earnin

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 crucial enabler for every financial service EarnIn provides its community members. We are going through transformative investments in machine learning platforms and algorithms. We seek experienced engineers to shape and execute the vision of bringing state-of-the-art capabilities to our machine-learning stack. The US base salary range for this full-time position is $272,700 - $333,300 + equity + benefits. Our salary ranges are determined by role, level, and location. This role will be hybrid in our Palo Alto HQ with two days a week in-person.

• 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.
• 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.
• Familiarity with data pipeline and workflow management tools.
• Strong communication and collaboration skills.
• Passion for learning and staying updated with the latest industry trends in machine learning and platform engineering.