- Plus 2
- Santa Clara, CA
- Full-Time
- 59 days ago
- $120,000 – $200,000
Software Engineer (SE / Sr SE), Data Infrastructure.
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Software Engineer (SE / Sr SE), Data Infrastructure: our view in 3 lines...
- The Role:This role is for a software engineer building data infrastructure for autonomous truck systems.
- The Person:The person will build vehicle-data recording, transfer, validation, cataloging, storage, and access systems, and improve data formats and lakehouse representations for replay, analytics, and machine learning.
- Requirements:The role requires modern C++ and Python, plus experience with high-throughput systems, indexing, serialization, compression, schema evolution, backward compatibility, and the company’s Quality Management System requirements.
About the role
Our autonomous-driving fleet generates petabyte-scale sensor and system data. In this role, you will own critical parts of the path that makes this data reliable and useful—from high-throughput recording on the vehicle to transfer, validation, cataloging, and efficient access for replay, analytics, and machine learning. You will work primarily in modern C++ and Python, solving systems challenges across resource-constrained vehicle computers and large-scale offline infrastructure. We welcome engineers from systems, robotics, storage, or data-infrastructure backgrounds; prior autonomous-vehicle experience is helpful but not required.
We are open to candidates at either the Software Engineer or Senior Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn.
Responsibilities:
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Design and evolve high-throughput C++ systems that continuously record vehicle sensor and runtime data, selectively capture events, and collect system telemetry while operating safely under CPU, memory, disk, and network constraints
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Build reliable Python data-plane services and libraries for vehicle-data transfer, ingestion, validation, domain-specific format conversion, metadata extraction, cataloging, and storage lifecycle management
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Evolve versioned vehicle-data formats and their C++ and Python APIs, including indexing, serialization, compression, schema evolution, and backward compatibility
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Evolve columnar and lakehouse representations and access APIs for vehicle data, improving scalability and performance for fleet-scale mining, replay, and analytics
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Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts

