ML Engineer

$150,000 - $175,000/Yr

Fundbox - New York, NY

Full-time - Mid Level

New York, NY

Credit Intermediation and Related Activities

About the position

The ML Engineer at Fundbox will be a key member of the MLOps team, responsible for managing the entire machine learning lifecycle, including data pipeline development, model training, deployment, and continuous integration and deployment (CI/CD) processes. This role requires collaboration with cross-functional teams to enhance machine learning operations and ensure the efficient deployment of AI models.

Responsibilities

• Design, develop, and implement robust, scalable systems for feature engineering to support both online and offline model inference.
• Build reliable and efficient deployment pipelines for machine learning models to ensure their smooth transition into production.
• Develop and maintain CI/CD pipelines to support continuous model updates and releases.
• Collaborate with data scientists to develop and refine features that enhance model performance.
• Establish comprehensive monitoring and logging systems to detect anomalies, drifts, or performance issues in deployed models.
• Work closely with DevOps and DataOps teams to integrate machine learning solutions with the broader technical infrastructure.

Requirements

• At least 5 years experience in MLops Engineering.
• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.
• Proven experience as a Machine Learning Engineer, or in software development with a focus on infrastructure and model deployment.
• Proficient in programming languages such as Python, Node.js, Java, or Scala.
• Strong SQL skills and experience with database technologies.
• Hands-on experience with containerization (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
• Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).
• Excellent communication and collaboration skills.
• Solid understanding of continuous integration and continuous deployment (CI/CD) best practices.

Nice-to-haves

• Previous Fintech experience is a plus!

Benefits

• Competitive Compensation, including equity with Fundbox in the form of restricted stock units
• Generous PTO policy to include vacation, sick time and more
• Monthly lunch budget
• Total wellness benefits, including individual annual budget, mental and physical health resources and more
• Personal and professional development budget
• Stipend to improve your home office setup
• Premium coverage for health plans offered from day one (some options covered at 100% for Employees)
• 401k, Life insurance and disability benefits