Staff Machine Learning Engineer - ML Algorithms

$272,700 - $333,300/Yr

Earnin - Palo Alto, CA

Full-time - Mid Level

Hybrid - Palo Alto, CA

Administrative and Support Services

About the position

EarnIn is seeking experienced machine learning engineers to innovate and set new standards in ML applications within the fintech industry. This role focuses on creating groundbreaking solutions using large language models, generative AI, and advanced machine learning algorithms, with the goal of generating substantial business and social impact. The position is integral to the company's mission of providing financial flexibility to its community members through real-time access to earnings.

Responsibilities

• 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 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.
• Mentor junior team members, offering guidance and technical expertise.
• Lead by example, fostering an environment of operational excellence and driving transformative change.

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 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 Anthropic; LLM guardrails, framework such as LangGraph, LangChain; ML flow.
• Strong communication and collaboration skills.
• Passion for continuous learning and staying updated on industry trends.

Benefits

• Equity options
• Comprehensive health benefits
• Flexible work schedule
• Hybrid work environment