Head of Engineering
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.