Senior Manager, Consumer AI Devices

About the role

This role defines future human-device interaction at the edge. The Senior Manager leads consumer AI devices through hardware innovation and product strategy. Decisions on build-buy partnerships shape the Samsung ecosystem across smartphones, wearables, and more.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

Global consumer trends and technical feasibility are combined to propose next-generation, AI-driven devices that redefine the Samsung ecosystem.

Requirements

The posting states a pay range of $198100 to $272500.

A Master's degree in Electrical Engineering, Computer Engineering, or related discipline or a PhD in hardware, sensors, or embedded systems is required. 7+ years of consumer electronics hardware research experience is required, with the last 2 3 years spent in technical product management or product strategy.

Deep expertise in consumer device architecture, including SoC design, RF systems, power management, and sensor fusion, must be demonstrated. A deep understanding of On-Device AI, AI accelerator architectures, edge computing constraints, and how AI models interact with physical hardware is essential.

Complex findings are conveyed clearly to diverse audiences, and hypothetical technical implementation impacts on hardware stacks are envisioned. Stakeholders are influenced effectively, and cross-functional, multi-team, and global projects are led without direct authority. Precision in written and verbal communication is maintained, with executive presentations delivered confidently. Effectiveness in ambiguous, fast-paced environments is required. A strong internal and external network within industry, startup, and venture communities is maintained. Domestic and international travel within 15 percent of time is mandatory.

Practical notes

The role is office-based and requires sitting and standing at a desk. Samsung provides equal employment opportunity and requires compliance with trade secret policies. Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Work connects hardware research, product strategy, and partnerships in consumer devices. Tools related to sensor technologies, AI accelerators, and novel computing platforms are central to the role. Navigation of a large corporate ecosystem with global stakeholders and cross-regional teams is required. Strategic vision is balanced with detailed technical assessment and business case development. Emerging technologies in consumer devices, wearables, XR, and smart appliances are engaged with regularly.

Questions to ask

Worth asking in any interview: how the team measures success, who the role works with daily, what the onboarding looks like, and what the company is trying to achieve this year. Asking what past hires did well is a strong final question. Keep the list short and pick the questions that matter most to you.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.