Hardware and Firmware Engineer, Robotics
MeckaBuild embedded Linux and Android software for Mecka’s robotics data systems. Improve camera capture, device reliability, performance, and recovery on physical hardware.
Open
Mecka builds infrastructure for Physical AI, helping robotics and embodied-AI teams turn real-world human activity into systems that can learn, be evaluated, and operate reliably outside the lab. Its Egoverse platform combines large-scale egocentric datasets with telemetry across vision, depth, tactile sensing, motion, and localization.
Through developer tools, APIs, and enterprise services, Mecka supports the evaluation and deployment of task-specific robotic systems. The company works with hardware OEMs, model developers, and commercial partners, providing the data and operational layer for robotics without manufacturing robots itself.
Hardware Engineer, Edge Machine Learning
Deploy computer vision models on embedded devices and build C++ inference pipelines for Mecka’s robotics and embodied AI data infrastructure.
Description
- Train and assess computer vision models for embedded deployment
- Develop efficient C++ inference pipelines and integrate them with embedded Linux software
- Tune models and runtime performance for latency, memory use, power consumption, and sustained operation
- Measure performance using representative data and hardware
- Trace errors across preprocessing, inference, and integration
Requirements
- At least five years of machine learning or computer vision experience, including deploying models on embedded or resource-constrained hardware
- Strong Python and C++ skills, including debugging and performance profiling
- Experience training and evaluating computer vision models with a framework such as PyTorch
- Experience developing software for embedded Linux
- Understanding of quantization, model conversion, and inference optimization on CPUs, GPUs, or NPUs
- Ability to assess accuracy, false positives, and missed detections across varying lighting, motion, and operating conditions
- Experience with accelerator runtimes, custom operators, or camera and video pipelines
- Experience curating datasets
Benefits
- Equity
- Health and wellness benefits
- Additional company programs
- Hybrid work arrangement
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