Director, Machine Learning Engineering

We are seeking a strategic and execution-oriented Director to lead our Runtime Intelligence & Personalization function. This leader will own the vision, strategy, and delivery of intelligent runtime systems that power context-aware, personalized experiences across products and platforms. This role sits at the intersection of AI/ML, platform engineering, and product strategy, responsible for building scalable systems that leverage context, memory, and retrieval to deliver differentiated, real-time intelligence.

Responsibilities

Define and execute the roadmap for runtime intelligence capabilities, including context building, memory systems, and RAG-based architectures; Translate business and customer needs into scalable, AI-powered personalization strategies; Partner with executive stakeholders to align runtime intelligence investments with enterprise priorities; Act as a thought leader in shaping next-generation personalization and AI-driven experiences; Lead development of core runtime capabilities including context orchestration, memory systems, retrieval systems, and personalization frameworks; Drive design and implementation of high-scale, low-latency systems; Establish observability standards across runtime intelligence systems; Define KPIs and metrics to evaluate system performance and business impact; Oversee end-to-end delivery of runtime intelligence platforms; Build, lead, and scale high-performing teams across engineering, ML, and platform functions; Partner with Product, Design, Data, and Infrastructure teams to deliver integrated solutions

Requirements

10–15+ years of experience in engineering, platform, or AI/ML roles, with significant leadership experience; Proven track record building and scaling distributed systems, AI platforms, or personalization systems; Deep expertise in Retrieval-Augmented Generation (RAG), context and memory architectures, real-time inference systems; Strong business acumen with the ability to translate strategy into execution; Demonstrated success leading large, complex, cross-functional initiatives

Nice to have

Experience with LLMs, generative AI, and agent-based systems; Background in observability, experimentation frameworks, or system optimization; Experience operating in high-scale, customer-facing environments

Benefits

Personalized development programs; Mentorship; Certification assistance; Inclusive and collaborative culture; Competitive pay, benefits, and flexibility