Head of Engineering

Algorized; Campbell (CA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

A fast-growing deep tech startup is seeking a hands-on engineering leader in Campbell, CA. This role involves managing and mentoring a high-performing technical team focused on embedded systems and edge AI/ML. The ideal candidate has over 15 years of experience in tech, with significant time in leadership roles, and will drive the engineering of scalable AI infrastructure. This opportunity allows for hybrid work, fostering a culture of technical excellence and accountability within a dynamic environment.

Qualifications

• 15 years of professional experience in tech with 5 years as a Product Engineering/Management leader.
• Experience with AI infrastructure and on-premises/hybrid products.
• Expertise in managing large-scale infrastructure teams and delivering projects.
• Experience leading and managing large-scale infrastructure teams, and delivering projects.

Responsibilities

• Lead, mentor, and expand a high-performing technical team.
• Drive engineering of scalable, sensor-agnostic edge computing platform.
• Define and implement a modular, scalable system architecture.
• Collaborate with cross-functional teams to define the product roadmap.
• Lead development of ML infrastructure and model deployment.
• Ensure technical delivery and validation with partners.
• Build a culture of technical excellence and accountability.

Skills

Embedded systems

Edge AI/ML

Scalable software architecture

Technical leadership

Mentoring teams

Radar signal processing

Education

Master’s degree or PhD in Engineering

Job description

Algorized is a fast growing deep tech startup redefining sensing and perception AI. Our sensor-agnostic software platform enables real-time human activity detection across automotive, healthcare, smart devices, and robotics.

We’re looking for a hands‑on engineering leader with deep expertise in embedded systems, edge AI/ML, and scalable software architecture—who can drive execution while building and mentoring a high‑performing team. You should thrive in fast‑paced environments, take full ownership, and turn complex technical challenges into real‑world, production‑ready solutions. If you are resourceful, have deep understanding in scaling edge AI/ML and ready to join a dynamic fast‑growing start‑up this unique opportunity is for you!

LOCATION

Hybrid/Campbell, CA

EMPLOYMENT TYPE

Full Time

Responsibilities

• Lead & Scale: Manage, mentor, and expand a world‑class technical team with expertise in embedded systems, radar signal processing, edge‑ML, and software architecture.
• Product Engineering Ownership: Drive the engineering of a scalable, sensor‑agnostic edge computing platform integrated on any wireless communication radar chip, multi‑modal sensor fusion—ensuring robust AI/ML models performance, real‑time processing, and algorithmic metrics KPIs.
• System Design: Define and implement a modular, scalable, and maintainable system architecture suitable for production‑level deployments.
• Collaborate Cross‑Functionally: Work closely with the CEO, CPO, researchers and sales to define product roadmap, align execution, and meet customer milestones.
• Build scalable ML/AI Tech Stack: Lead hands‑on development and architecture efforts across ML Infrastructure & Model Deployment.
• Customer‑Facing Validation: Ensure technical delivery and validation with early adopters and enterprise partners.
• Process & Culture: Build a culture of technical excellence, ownership, and execution. Set high standards for code quality, agile practices, and documentation, while fostering a make‑it‑happen mindset and strong team accountability.

Qualifications

Minimum Qualifications

• 15 years of professional experience in tech, including 5 years of experience as a Product Engineering/Management leader with a research background.
• Experience with platforms and large‑scale AI infrastructure and on‑premises/hybrid products.
• Experience with general purpose systems and infrastructure, and with technical innovation in hardware and on‑premises infrastructure.
• Experience leading and managing large‑scale infrastructure teams, and delivering projects.

Preferred Qualifications

• Master’s degree or PhD in Engineering.
• Experience leading Product, Engineering, and Research teams in complex, cross‑functional environments.
• Experience innovating state‑of‑the‑art technology at scale within large, complex, and cross‑functional engineering environments, and a passion for development and the use of cross‑platform shared code.
• Ability to balance detailed, technical guidance with “big picture” strategy, enabling teams to deliver products that are effective and also creating new ways to manage data at scale.