Machine Learning Engineer

Responsibilities

• In this role, you’ll:
• Partner with product, UX, and technical stakeholders to analyze business problems, clarify requirements, define scope, and translate them into measurable ML problem statements.
• Design, implement, and maintain scalable, enterprise-grade ML solutions in production.
• Build reproducible ML workflows for data preparation, training, evaluation, and inference using modern orchestration and MLOps tooling.
• Implement monitoring and evaluation frameworks to continuously improve data quality, model performance, latency, and cost through feedback loops.
• Partner cross-functionally with Product, Data Science/ML, Engineering, and Security to deliver resilient, scalable, and compliant ML-powered services.
• Demonstrate end-to-end systems understanding and articulate the “why” behind model and system design choices.
• Own operational excellence: SLAs, on-call, incident response, customer feedback triage, and blameless post-mortems.
• Drive engineering excellence via AI-assisted SDLC, code reviews, automated testing, MLOps best practices, knowledge-sharing, and mentoring.
• Actively adopt AI-assisted practices to improve implementation and collaboration efficiency.