Member of Technical Staff - ML Data Infrastructure

About the role

Mimetic Machines builds learning and deployment environments for physical AI, capturing skilled work in real workplaces to help robots learn. This is a founding role in Munich, Germany, where you will own the systems that turn recordings into training-ready datasets: from recording and upload through storage, processing, quality review and delivery. You will set the architecture, build the systems and work directly with the founders.

Key responsibilities

• Own the data platform from capture to training-ready datasets and delivery.
• Build reliable recording, offload and upload workflows that recover from interrupted sessions and unreliable networks.
• Design ingestion contracts for different camera configurations and modalities.
• Build processing pipelines for validation, reconstruction, annotation and other transformations, with scheduling, retries and recovery.
• Make datasets reproducible through versioning and provenance across recordings, outputs, annotations and exports.
• Work with researchers to produce useful dataset formats, subsets and training inputs.
• Make pipeline health, processing cost and data loss visible, and work with capture and field operations to fix problems at their source.

Required profile

• Has owned a production pipeline for video, media, sensor data or large ML datasets and can explain the decisions and trade-offs made.
• Understands object storage, asynchronous processing, retries and what happens when a system fails partway through.
• Measures correctness, cost and throughput and uses them to decide what to improve.
• Able to turn an ambiguous objective into a concrete plan and make iterative progress independently.
• Takes responsibility for the outcome, from first implementation through operation and improvement.

Required skills

• Experience in one or more of: video encoding and compression, multi-camera or multimodal data, dataset formats and sharding, GPU processing, annotation tools, cloud infrastructure, workflow orchestration or systems programming.
• No need for every area; strong engineering judgment and ability to learn and keep systems running are valued.

To apply, send your CV and links to work by email, mentioning a data system you owned, what it handled, where it failed and what you changed.