Software Development Engineer II, Search

Mapbox

46d•$160,650 - $217,350•Remote

About The Position

The Search Box - Offline Search team is responsible for building a robust, high-performance search engine that empowers mobile and automotive customers to find places, addresses, and points of interest seamlessly, even in environments with zero network connectivity. We do this by engineering highly optimized on-device search algorithms, developing advanced data compression and efficient delta update mechanisms, and creating lightweight, scalable tile-based solutions that deliver low-latency results on constrained hardware. Our work ensures that users—from drivers navigating remote highways to mobile users in dense urban dead zones—experience a reliable, fast, and consistent search experience wherever they go. As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow. Joining us as a Software Engineer on the Offline Search team, you will play a critical role in bringing world-class search capabilities to embedded systems and mobile devices operating without network connectivity. You will bring your expertise in systems engineering and performance optimization to a passionate, cross-functional team focused on the automotive and mobile mapping space.

Requirements

Bachelor's or Master's degree in Computer Science, Software Engineering, or equivalent practical experience.
Strong proficiency in C++ (our core engine language), with a solid understanding of memory management, multi-threading, and systems-level programming.
Experience with Python or other scripting languages commonly used for tooling, data processing, or test automation.
Proven experience analyzing and optimizing code for performance-constrained environments, thoughtfully balancing tradeoffs between CPU utilization, memory consumption, and query latency.
Familiarity with data structures, algorithmic efficiency, and binary data formats (experience with data compression like Zstd or delta update mechanisms is a strong plus).
Strong analytical thinking and the ability to justify technical decisions using system telemetry and data.
Meticulous attention to detail and a creative, resourceful approach to problem-solving.
Excellent communication skills in English, with a proven ability to collaborate effectively across cross-functional engineering, product, and data teams.

Nice To Haves

Prior experience in the mapping, navigation, or automotive industry.
Knowledge of machine learning techniques for geospatial data analysis.
Contributions to open-source geospatial or data analysis projects.

Responsibilities

Design, code, and optimize core search algorithms tailored for on-device execution, ensuring high-speed query resolution under strict CPU, memory, and storage constraints.
Take ownership of complex offline data delivery systems, designing and implementing advanced tile compression techniques (e.g., Zstd) and efficient delta update pipelines to minimize payload sizes.
Collaborate across multiple R&D and backend teams to seamlessly integrate data processing pipelines and ensure parity between our cloud and offline search products.
Engage directly with trend-setting automotive OEMs in EU, US, Japan, and China, as well as suppliers like automotive Tier 1 companies and Mapping firms to understand hardware specifications, troubleshoot integration challenges, and align technical deliverables with their rollout schedules.
Collect and monitor deep system telemetry to evaluate performance tradeoffs (e.g., CPU utilization vs. query latency), establish baselines, and drive continuous architectural improvements.
Play a key role in defining the technical roadmap, scoping complex features, and writing technical design documents for next-generation offline search capabilities.