At January, we're transforming the lives of consumers by bringing humanity to consumer finance. Our data-driven products help financial institutions streamline their collections, offering borrowers straightforward and compassionate solutions to regain financial stability and control over their lives. We're not just expanding access to credit – we're restoring dignity and giving millions of people the chance to achieve financial freedom.
As a Senior ML Platform Engineer, you'll be instrumental in building and maintaining the infrastructure that powers January's machine learning systems. Working closely with data scientists, engineers, and product teams, you'll create scalable and reliable ML systems that enable us to better serve our customers.
Design and implement MLOps architecture, including selecting and integrating best-in-class tools for model tracking, deployment, monitoring, and automated retraining pipelines
Build automated CI/CD pipelines for ML models with robust testing, error detection, and rollback capabilities, ensuring reproducible deployments across both real-time inference services and batch prediction pipelines
Create comprehensive monitoring and alerting systems to track model performance, data quality & drift detection, enabling quick identification and resolution of production issues
Design and implement systems for model versioning and experimentation that enable data scientists to rapidly iterate and validate their work
Build scalable feature computation pipelines that ensure consistency between training and inference, while optimizing for cost and performance
Evaluate and integrate new tools and technologies that can improve our ML infrastructure and development workflows
Experience building and scaling ML infrastructure in cloud environments, with strong knowledge of containerization and infrastructure-as-code
Track record of implementing monitoring and observability systems for production ML workloads
Proficiency in Python and modern software development practices, with experience in ML frameworks and deployment patterns
Strong problem-solving skills with the ability to balance quick solutions with long-term architectural decisions
Experience collaborating with data scientists and product managers to implement best practices for ML development
As a New York City-based company, we are dedicated to transparent, fair, and equitable compensation practices that reflect our commitment to fostering an environment where all team members are valued and supported. We encourage individuals from all backgrounds to apply.
We are an equal opportunity employer committed to diversity and inclusion in the workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, age, veteran status, or any other legally protected characteristic.
Yearly based
New York City