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Lead Edge AI Engineer

Weekday AI

San Francisco, California, United States Remote permanent

Posted: January 14, 2026

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Quick Summary

We're building the foundational data infrastructure for an edge-first world—where intelligence lives not in distant clouds but across billions of devices, vehicles, robots, and satellites. As a Lead Edge AI Engineer, you'll be responsible for designing and implementing AI solutions that meet the needs of our clients, while ensuring the integrity and security of our data.

Job Description

This role is for one of the Weekday's clients

Min Experience: 4 years

Location: Bay Area, North America, Europe

JobType: full-time

We’re building the foundational data infrastructure for an edge-first world—where intelligence lives not in distant clouds but across billions of devices, vehicles, robots, and satellites. AI is moving closer to where data is created, enabling compute that is instant, private, and verifiable. Yet the edge remains fragmented, forcing developers to trade off performance for convenience, privacy for usability, and autonomy for control.

As a Lead Edge AI Engineer, you will own the edge-AI engineering roadmap and make developing at the edge as natural and powerful as building in the cloud. You’ll design the systems that let developers deploy, orchestrate, and verify AI models across edge environments—from federated learning and on-device inference to adaptive compute pipelines on heterogeneous hardware.

This role sits at the intersection of distributed systems, AI infrastructure, and edge computing, combining model execution, verifiable computation, and developer experience. You’ll work closely with research, product, and infrastructure teams to define standards for how AI operates in decentralized, privacy-preserving networks.


Requirements:
Responsibilities

• Architect and prototype edge-AI pipelines enabling local training, inference, and cross-device collaboration.
• Build developer-friendly APIs and SDKs that abstract distributed complexity into efficient, elegant experiences.
• Optimize performance across constrained and diverse hardware—including GPUs, NPUs, and embedded accelerators.
• Integrate edge-first data flows with privacy-preserving and verifiable computation frameworks.
• Collaborate with product, research, and infrastructure teams to shape the developer experience for edge-native AI.
• Mentor engineers and help build a culture focused on precision, performance, and trust.

Requirements

• Deep experience in AI/ML systems and model deployment in real-world edge environments.
• Strong proficiency in Rust, Go, C++, or Python.
• Familiarity with distributed systems, federated learning, or privacy-preserving AI.
• Understanding of edge compute hardware and runtime constraints.
• Experience in a startup or scale-up environment.
• Proven track record of delivering complex distributed or AI systems end-to-end.
• Curiosity for verifiable computing, zero-trust architectures, and data-centric AI design.
• A first-principles mindset—you care about building foundational systems that last decades.

Why This Role Matters
This is a rare opportunity to define the foundation for edge-native AI. You’ll shape how intelligence operates across billions of devices—from chips to constellations—building deep infrastructure that enables verifiability, privacy, and autonomy in AI systems. If you’ve ever wanted to create the data layer powering the edge-first future of AI, this is your chance.

Skills
Lead Edge AI Engineer, Rust, Go/Golang, Python, C++, Distributed Systems, Federated Learning, Edge Computing

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