Machine Learning Engineer II
Core
Building robust, cost-effective, and high-performance backend systems and MLOps infrastructure to power scalable data-science solutions and feature-extraction applications.
Role type
Machine Learning Engineer II (Backend Systems & MLOps)
Builds
Centralized feature stores, auto-training frameworks, in-house model serving systems, real-time monitoring tools, and standalone feature-extraction applications.
Domain
Financial services technology / Distributed systems engineering
Deliverable
production ML models | infrastructure
Required skills
Java, Python, Go, or Kotlin; object-oriented design; algorithm design; distributed systems troubleshooting; performance optimization; system observability; unit testing; design documentation.
Preferred skills
Event-driven architectures (Kafka, RabbitMQ); security best practices for APIs; mentoring junior engineers.
Technologies
Kafka, RabbitMQ
Responsibilities
Design and implement algorithms for complex real-world problems; build and optimize backend systems for scalability and cost-efficiency; troubleshoot and optimize distributed systems; improve team standards through code reviews and feedback.
Seniority
Mid-level IC (3+ years experience)
