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Bright Vision Technologies Himalayas · Posted 2d ago

Edge AI Engineer

USD Full time Remote

Mid-level Edge-AI-Engineer, Senior-Edge-AI-Engineer, Edge-AI-Engineering, Edge-Computing-Engineer, ML-Edge-Engineer, Edge-ML-Engineering, Software-Engineer-(AI) Himalayas
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Indexed description

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We are looking for a skilled Edge AI Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.

Requirements

  • Design and implement edge AI solutions optimized for diverse hardware including mobile SoCs, NPUs, and embedded accelerators.
  • Apply quantization, pruning, distillation, and architectural optimization to fit models within edge constraints.
  • Tune model performance for latency, energy efficiency, and memory footprint on target hardware.
  • Build cross-platform inference runtimes leveraging frameworks such as TensorFlow Lite, ONNX Runtime, and Core ML.
  • Optimize models for specific accelerator backends including DSPs, NPUs, and mobile GPUs.
  • Implement on-device model update, versioning, and rollback workflows that allow safe staged rollouts to large device populations and rapid recovery if a model release behaves unexpectedly in the field.
  • Design hybrid edge-cloud architectures that gracefully degrade based on connectivity and device capability.
  • Build telemetry pipelines that respect privacy while enabling continuous improvement.
  • Collaborate with hardware, firmware, and product teams to align AI capabilities with device constraints.
  • Implement secure execution paths, model protection, and integrity verification on edge devices.
  • Develop benchmarking suites that characterize accuracy, latency, and energy trade-offs across devices.
  • Drive responsible AI considerations including on-device privacy and bias evaluation.
  • Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
  • Stay current with edge AI hardware and software developments, regularly review release notes and community discussions, and translate noteworthy advances into concrete recommendations and adoption proposals for the team.

Benefits

  • Competitive base salary commensurate with experience, plus benefits

Originally posted on Himalayas

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