Software Engineer - AI Infrastructure
Mimic Robotics- Location
- Zürich
- Workplace
- Onsite
- Employment
- Full Time
- Salary
- —
Posted 3mo ago
About mimic
mimic robotics is an early stage deep tech robotics & AI start-up based in Zurich and supported by leading VCs. We give industry workers a helping hand for tedious manual labor tasks and mitigate labor shortages with a versatile automation platform. Our automation solutions, driven by dexterous robotic hands and cutting edge AI trained on human observations, bring a new level of AI embodiment to the real world.
The Role
As a Software Engineer - AI Infrastructure, you'll join a small, high-impact team that builds the systems connecting data collection, training, and deployment into a coherent platform. You'll work across data pipelines, internal tooling, and visualization, shipping real features from day one as we build out the production ML infrastructure behind a robotics company pushing the boundaries of what's possible with dexterous manipulation.
Responsibilities
- Scale and improve data processing pipelines that handle robotics data at growing scale, from ingestion through quality checks to training-ready datasets
- Build and maintain data quality tooling, including anomaly detection, validation checks, and profiling, to ensure our data meets the standards required for training
- Develop and maintain internal visualization tools, improving how the team and researchers inspect, understand, and qualify data
- Write well-tested, well-documented code that is easy for others to maintain and extend
Requirements
- Strong Python fundamentals: You write clean, readable, well-structured code and understand data structures and performance tradeoffs.
- Strong Software Engineering foundations: You understand and work consistently with Git and Github, focusing on writing modular and maintainable code and proactively think of high-level refactors to keep systems understandable, well-scoped and clear.
- Strong foundation in data engineering concepts: familiarity with ELT/ETL pipeline design, storage formats, and data quality practices for validation, anomaly detection, or statistical profiling.
- You're a clear communicator who can explain technical decisions, collaborate across teams, and keep people informed without being asked.
- You’re proactive and motivated to contribute meaningfully while learning from those around you.
- You're genuinely excited about robots that learn from real-world data.
Nice to Have
- Experience with robotics or sensor data (video, point clouds, time series from physical systems).
- Experience with web frameworks (FastAPI) or frontend tools (React).
- Experience with ML Infra fundamentals: Pytorch, dataloading, training loop, profiling, inference.
Skills
- Machine Learning
- Python
- Git
- GitHub
- ELT
- ETL
- FastAPI
- React
- PyTorch
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