Staff Machine Learning Engineer (Applied ML) at EarnIn

Mountain View, California, United States

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$272,700 – $333,300Compensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

FintechIndustries

Requirements

Bachelor's or Master’s degree in Computer Science, Engineering, or a related field
7+ years of experience in machine learning with strong software engineering skills
Proficiency in a broad range of ML techniques including 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: foundation models and APIs such as OpenAI and Anthropic; LLM guardrails, frameworks such as LangGraph, LangChain; MLflow
Strong communication and collaboration skills
Passion for continuous learning and staying updated on industry trends

Responsibilities

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

Skills

Key technologies and capabilities for this role

Machine LearningLarge Language ModelsGenerative AIA/B TestingML DeploymentFintech ML

Questions & Answers

Common questions about this position

What is the salary range for this Staff Machine Learning Engineer position?

The base salary range for this full-time position in Mountain View is $272,700 - $333,300 plus equity and benefits.

Is this a remote position, or does it require office work?

This is a hybrid position in Mountain View that requires in-office work 2-3 days a week.

What skills and experience are required for this role?

Candidates need a Bachelor's or Master’s degree in Computer Science or related field, 7+ years in machine learning with strong software engineering skills, proficiency in ML techniques like deep learning, sequence models, and tree-based models, advanced Python skills, and experience with ML frameworks such as TensorFlow or PyTorch and cloud platforms like AWS Sagemaker.

What does the team work on at EarnIn?

The team designs, develops, A/B tests, and deploys risk models, enhances credit and fraud models with innovative features, monitors model health, explores deep learning in risk domains, and leads operational excellence while expanding to new products.

What makes a strong candidate for this Machine Learning Engineer role?

A strong candidate has 7+ years of ML experience with strong software engineering, proficiency in advanced ML techniques like deep learning and tree-based models, advanced Python and ML frameworks like TensorFlow/PyTorch, and hands-on experience with cloud ML platforms.

EarnIn

Provides early wage access without fees

About EarnIn

Earnin allows individuals to access their earned wages before payday without any fees or interest. Users can cash out a portion of their earnings and benefit from features like the "Balance Shield," which helps maintain their bank account balance. Unlike traditional financial institutions, Earnin operates on a model where users choose how much to pay for the service, fostering a community-driven approach. The company's goal is to create a fairer financial system that prioritizes accessibility and mutual support.

Palo Alto, CaliforniaHeadquarters

2012Year Founded

$184.9MTotal Funding

SERIES_CCompany Stage

FintechIndustries

201-500Employees

Benefits

Life in balance - Ten company holidays and flexible time off so you can rest and recharge when you need it most. With pay, no catch.

Family matters - When your family grows, we want your focus on them. Our generous parental leave policy and wellness funds make it easy to put yourself and loved ones first.

Learn & grow - A commitment to career development that includes regular training for team members and managers alike, 360 feedback, and an annual stipend for growth opportunities.

Company culture - Employee Resource Groups provide growth opportunities and allow you to create the company you want to work at (more on that below).

Health & wellness - Flexible healthcare options across medical, dental, and vision—and a free Employee Assistance program offering mental health resources and legal advice.

Save & support - Includes Earnin’s 401(K) and FSA plans with tax advantages for retirement, healthcare, and dependent care expenses.

Risks

Legal challenges from deceptive lending allegations could harm Earnin's reputation.

Increased competition in early wage access may impact Earnin's market share.

Reliance on voluntary contributions may not sustain long-term revenue.

Differentiation

Earnin offers fee-free early wage access, unlike traditional payday loans.

Users choose their payment amount, fostering a community-driven financial model.

Balance Shield feature provides automatic deposits to prevent overdrafts.

Upsides

Earnin has facilitated over $15 billion in earnings access since 2013.

Recognition as Best Payments App highlights Earnin's fintech innovation.

Partnerships with gig platforms could expand Earnin's user base.

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