Machine Learning Engineer

About the role

- Partner with business and product teams to identify high-impact opportunities and translate ambiguous requirements into GenAI-powered features and workflows delivered through a shared AI platform and embedded across products - Design, build, and own end-to-end GenAI capabilities that support both a centralized AI platform and product teams, covering all aspects from prompt and tool design to agent orchestration, retrieval strategies, model selection, and system evaluation - Develop reliable, scalable, and cost-aware GenAI features in collaboration with platform, data, and application engineering teams, ensuring strong performance, observability, and maintainability in production environments - Establish evaluation and monitoring strategies for GenAI-driven features, focusing on output quality, correctness, safety, and business relevance through offline benchmarks, automated checks, and human-in-the-loop review - Develop Text-to-SQL and structured reasoning capabilities that enable natural-language interaction with structured data, ensuring accuracy, security, and alignment with business semantics - Leverage agentic AI patterns (multi-step reasoning, tool use, planning, memory, feedback loops) to support complex workflows, while establishing guardrails for reliable and predictable behavior - Communicate trade-offs, system behavior, and limitations clearly to technical and non-technical stakeholders, enabling informed product and business decisions - Continuously research, prototype, and operationalize emerging GenAI techniques to improve platform capabilities and accelerate adoption across teams