2 дня назад
Director, Machine Learning Engineering (AI)
150 000 - 300 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Director, Machine Learning Engineering (AI): Building scalable runtime intelligence and personalization platforms with an accent on context orchestration, memory systems, retrieval-augmented generation, and real-time inference. Focus on leading distributed systems delivery, optimizing latency and response quality, and scaling cross-functional AI/ML and platform engineering teams.
Location: Palo Alto, CA, United States
Annual salary: $150,000–$300,000
Company
is a large United States auto insurer and a member of the Berkshire Hathaway family of companies.
What you will do
- Define and execute the roadmap for runtime intelligence, context building, memory systems, and RAG-based architectures.
- Lead the development of context orchestration, state management, retrieval, and personalization capabilities.
- Drive the design and implementation of high-scale, low-latency, secure, observable, and reliable systems.
- Establish observability standards, performance metrics, feedback loops, and continuous optimization practices.
- Oversee end-to-end platform delivery and cross-functional execution across engineering, data science, product, design, data, and infrastructure.
- Build and scale engineering, ML, and platform teams through hiring, coaching, and organizational design.
Requirements
- 10–15+ years of experience in engineering, platform, or AI/ML roles with significant leadership experience.
- Proven experience building and scaling distributed systems, AI platforms, or personalization systems.
- Deep expertise in Retrieval-Augmented Generation, context and memory architectures, and real-time inference systems.
- Strong business acumen and experience translating strategy into execution.
- Demonstrated success leading large, complex, cross-functional initiatives.
- will not sponsor a new applicant for employment authorization for this position.
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.
Culture & Benefits
- Inclusive and collaborative culture focused on shared success.
- Personalized development programs, mentorship, and certification assistance.
- Competitive pay, benefits, and flexibility supporting employee well-being.
- Environment emphasizing innovation, integrity, accountability, and continuous improvement.
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