Software Engineer - Compression

Mosaico is an open-source data platform for robotics and physical AI. We’re solving a hard infrastructure problem: the tools that exist today for storing, indexing, and retrieving high-frequency sensor data are either too primitive or too painful to work with at scale.

We’re building the missing piece, and doing it in the open. Apache 2.0 licensed, public roadmap, real community. We care about the codebase being something people actually want to read and contribute to, not just use. In Italy, companies that operate this way are still a rarity, and we think that’s exactly what makes this interesting.

We’re based in Reggio Emilia, working with teams in defence, automotive, and agritech, and we’re building a commercial offering on top of the open-source core.

The role

Mosaico stores and transfers high-frequency, multimodal sensor data: point clouds, video streams, images, and dense time series from dozens of concurrent sensors. Compression is not an afterthought in this context, it is a core part of what makes the platform viable at scale.

We’re looking for a Senior Software Engineer with deep expertise in compression to analyse, select, and implement the right compression strategies for each data type inside mosaicod. That means understanding the tradeoffs between compression ratio, encoding and decoding latency, and CPU cost for each data modality, and knowing which existing formats and algorithms are the right fit. It also means understanding how compression interacts with network transfer: bandwidth constraints, streaming behavior, and how data moves efficiently between a robot and the platform or between the platform and downstream consumers.

The work is in Rust, lives inside mosaicod, and is built in the open under Apache 2.0.

What you’ll work on

• Analyse compression requirements and tradeoffs for each data type in the platform: point clouds, video, images, and generic time series
• Select and implement compression strategies for each modality based on real performance and bandwidth measurements
• Study and optimise network transfer patterns to ensure efficient data movement under varying bandwidth conditions
• Integrate compression and decompression into the mosaicod ingestion and retrieval pipeline
• Contribute to the open-source codebase and participate in technical discussions with the community

What we’re looking for

• Strong Rust, production-grade and used in a systems context
• Deep knowledge of compression algorithms and formats across multiple data modalities: general purpose (zstd, lz4, snappy), time series, point clouds, image and video codecs
• Solid understanding of how compression interacts with network transfer, bandwidth, and streaming
• Ability to evaluate and benchmark compression strategies empirically, not just theoretically
• Experience integrating compression into production data pipelines or storage systems
• Autonomous and rigorous, able to drive analysis and implementation decisions in a small team
• Fluent in English, written and spoken

Nice to have

• Familiarity with Apache Arrow and columnar compression techniques
• Experience with point cloud formats
• Background in video or image codec internals
• Experience with network optimization for high-throughput data transfer
• Open-source contributions in the compression or systems space

What we offer

• A technically deep problem that matters directly to the performance and scalability of the platform
• A codebase where your work on compression will be visible in every ingestion and retrieval operation
• Work that ships as open source under Apache 2.0 and powers a commercial product
• Flexible hours, full remote with optional office access in Reggio Emilia
• Competitive salary, discussed openly based on your level and experience
• Welfare package
• Stock options

Salary range

€70K – 100K, adjusted based on location, experience, and level.

Contacts

Interested? Write to [email protected]

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