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Mecka
Mecka
11 – 50 Zaposleni
PodjetjeSaaSUmetna inteligenca

Mecka razvija infrastrukturo za fizično umetno inteligenco ter ekipam na področju robotike in utelešene umetne inteligence pomaga pretvarjati človekove dejavnosti v resničnem svetu v sisteme, ki se lahko učijo, jih je mogoče vrednotiti in zanesljivo delujejo zunaj laboratorija. Njena platforma Egoverse združuje obsežne egocentrične nabore podatkov s telemetrijo vida, globine, tipnega zaznavanja, gibanja in lokalizacije.

Mecka z razvojnimi orodji, API-ji in poslovnimi storitvami podpira vrednotenje in uvajanje robotskih sistemov za specifične naloge. Podjetje sodeluje s proizvajalci strojne opreme, razvijalci modelov in komercialnimi partnerji ter zagotavlja podatkovni in operativni sloj za robotiko, ne da bi samo izdelovalo robote.

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Delovna mesta v podjetju

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.

CAKanada
170.000 $ – 190.000 $ / leto
HibridnoPolni delovni časSrednja ravenSeniorZahtevani Jezik: angleščinaInženir strojne opreme
C++LinuxPythonPyTorch

Opis

  • 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

Zahteve

  • 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

Ugodnosti

  • Equity
  • Health and wellness benefits
  • Additional company programs
  • Hybrid work arrangement

Sorodna delovna mesta