The Role
As a Software Engineer for AI Infrastructure, you will build data pipelines, maintain data quality tooling, and develop internal visualization tools while writing clean, maintainable code.
Summary Generated by Built In
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 Required
- Strong Python fundamentals
- Strong Software Engineering foundations
- Strong foundation in data engineering concepts
- Clear communication skills
- Proactive and motivated attitude
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The Company
What We Do
Physical AI to scale your most tedious tasks from manufacturing to logistics. Our robots intuitively learn new skills from you and operate autonomously in any environment.
