Backend Engineer

Job Description

At Fundbox, we are dedicated to supporting small businesses through fast and incredibly intuitive access to working capital. With our embedded technology solutions, we've cultivated deep partnerships with industry-leading software to give small businesses financial agility and peace of mind. We need outstanding people to help us achieve our goals.
We are seeking a talented and experienced engineer to join our MLOps team. In this role, you will play a crucial part in all Machine Learning lifecycle operations, offline and online feature serving for AI models, Data pipeline for ML, Model training, CI\CD for AI models, and more. As a key member of the MLOps team, you will collaborate with cross-functional teams to streamline the end-to-end machine learning lifecycle and contribute to optimizing our MLOps processes.
Applicants must be currently authorized to work in the United States on a full-time basis without the need for employer sponsorship. Fundbox will not hire any applicants for this role who require employer sponsorship for a non-immigrant visa.

In this role, you will

• ML Data Pipelines: Design, develop, and implement robust, scalable systems for feature engineering to support both online and offline model inference.
• Model Deployment: Build reliable and efficient deployment pipelines for machine learning models to ensure their smooth transition into production.
• CI/CD for ML Models: Develop and maintain CI/CD pipelines to support continuous model updates and releases.
• Feature Engineering: Collaborate with data scientists to develop and refine features that enhance model performance.
• Monitoring & Quality Assurance: Establish comprehensive monitoring and logging systems to detect anomalies, drifts, or performance issues in deployed models.
• Collaboration: Work closely with Dev Ops and Data Ops teams to integrate machine learning solutions with the broader technical infrastructure.

You should have

• 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, Sage Maker).
• Excellent communication and collaboration skills.
• Solid understanding of continuous integration and continuous deployment (CI/CD) best practices.
• Previous Fintech experience is a plus!

Diversity and Inclusion at Fundbox

We're proud to be an equal-opportunity workplace as we know that diverse teams produce the best work. We're committed to building a culture of innovation and inclusion across gender, race, age, sexual orientation, religion, disability, and identity. Here at Fundbox, we strive to uphold a system of values we call MOSAIC: Mission, Ownership, Speed, Achva (a Hebrew term meaning to help one another), Innovation, and Clarity. Embracing our diverse backgrounds and abilities allows us to harness our creativity and achieve more, together.

Compensation & Benefits

We anticipate the NY base salary range for this full-time position is $150,000 - $175,000 The range displayed on each job posting reflects the amount the employer reasonably expects to pay for this position across all US locations. Within this range, individual pay is determined by work location and additional factors (i.e. job-related skills, experience, and relevant education or training). The compensation details listed in US role postings reflect the base salary only and do not include any bonuses, equity, or benefits.
Fundboxers (as we like to call them) join our amazing team due to our mission of empowering small businesses to realize their full potential with the help of Fundbox.

We offer incredible benefits including:

• 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

Let's not forget, we were recently certified by Great Place to work with an employee satisfaction rate of 94%.