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обновлено 2 месяца назад

Edge AI MPU Product Manager (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
US

Описание вакансии

Текст:
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TL;DR

Edge AI MPU Product Manager (AI): Defining and executing product strategy for AI-enabled edge MPUs, bridging market needs with engineering innovation for smart devices. Focus on collaborating on architecture decisions, solving system-level challenges, and driving market leadership in Industrial IoT, Automotive, and emerging edge applications.

Location: Onsite in Austin, Oakhill Office, United States. This role requires domestic and international travel.

Company

hirify.global N.V. is a world leader in secure connectivity solutions for embedded applications, enabling a smarter, safer, and more sustainable world.

What you will do

  • Define and own the product vision and roadmap for AI-enabled edge MPUs, aligning with market trends and customer needs.
  • Translate market problems into clear PRDs, feature specs, and phased roadmaps; make data-driven trade-offs.
  • Collaborate with engineering on architecture decisions and innovations for heterogeneous compute, AI acceleration, and multi-modal pipelines.
  • Lead cross-functional teams (engineering, go-to-market, sales, applications, operations) throughout the product lifecycle.
  • Develop competitive positioning, value propositions, and go-to-market strategies for Industrial, IoT, and Automotive segments.
  • Build data-driven business cases and pricing strategies that deliver revenue growth and market share.

Requirements

  • BS in Computer Science, Electrical, or Computer Engineering.
  • 10+ years in product management, product marketing, or systems engineering for MPUs, SoCs, or embedded systems.
  • Demonstrated ability to turn customer requirements into actionable specs for hardware, software, and systems teams.
  • Strong understanding of heterogeneous compute architectures (CPU/GPU/NPU/DSP), memory systems, and interconnects.
  • Solid understanding of Artificial Intelligence (AI) and Machine Learning (ML) concepts, algorithms, frameworks, and toolchains.
  • Familiarity with edge AI applications, including computer vision, natural language processing, and sensor fusion in embedded systems.

Nice to have

  • Understanding of embedded safety concepts (ASIL/SIL), reliability, and security.
  • Experience with embedded software development, operating systems (Linux, RTOS), and developer toolchains.
  • Exceptional communication, presentation, and people skills, with the ability to influence and collaborate effectively.

Culture & Benefits

  • Access to online and offline learning opportunities for career development.
  • Commitment to sustainability and measurable year-on-year progress.
  • Inclusive work environment with programs focused on diversity, inclusion, and equality.
  • Opportunity to influence technology that transforms industries.