Remote Senior Machine Learning Engineer - Risk Modeling

Description:

• EarnIn is a pioneer in earned wage access, focusing on providing real-time financial flexibility for individuals living paycheck to paycheck.
• The company is experiencing rapid growth and is looking to hire world-class talent to support its expansion.
• The Senior Machine Learning Engineer will play a crucial role in developing innovative financial risk modeling solutions that have significant business and social impact.
• Responsibilities include designing, developing, A/B testing, and deploying risk models, collaborating with data scientists, enhancing credit and fraud models, monitoring model health, integrating advanced technologies, and leading operational excellence.
• The position offers a base salary range of $209,000 - $255,400, plus equity and benefits, and is fully remote.

Requirements:

• A Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent industry experience is required.
• Candidates must have at least 4 years of machine learning experience with strong software engineering skills.
• Experience in risk modeling for financial use cases is mandatory.
• Proficiency in machine learning techniques, including LLMs, deep learning, sequence, and tree-based models is essential; knowledge of credit/fraud risk and portfolio management is a plus.
• Advanced skills in Python programming, SQL, and data manipulation are required.
• Familiarity with machine learning frameworks such as TensorFlow and PyTorch, as well as cloud platforms like AWS Sagemaker, Databricks, and GCP Vertex AI, is necessary.
• Excellent communication and collaboration abilities are essential for this role.
• A passion for continuous learning and personal growth in a dynamic work environment is expected.

Benefits:

• The position offers a competitive base salary along with equity options.
• Employees will have access to a range of benefits, although specific details are not provided in the job description.
• EarnIn promotes a diverse and inclusive work environment, celebrating various backgrounds and perspectives within the team.