Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

Job Summary We are seeking an Edge Computing AI Engineer to design, optimize, and deploy machine learning models that run on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. The role focuses on model compression, quantization, and hardware-aware optimization, combined with strong systems engineering skills to ship reliable AI capabilities outside the data center. The ideal candidate has shipped edge AI in production where compute, memory, energy, and connectivity constraints shape engineering trade-offs.

Required Qualifications - Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field - 6+ years of ML engineering experience with edge or mobile AI - Strong proficiency in Python and C++ - Hands-on experience with model compression, quantization, and pruning - Experience with at least one major edge inference framework - Solid understanding of mobile and embedded hardware architectures - Experience deploying ML models to production on mobile or embedded platforms - Strong performance engineering and profiling skills - Familiarity with on-device privacy and security considerations - Strong communication and cross-functional collaboration skills

Preferred Qualifications - Experience with custom NPU or DSP toolchains - Familiarity with federated learning or on-device personalizatio

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

Job Summary We are seeking an Edge Computing AI Engineer to design, optimize, and deploy machine learning models that run on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. The role focuses on model compression, quantization, and hardware-aware optimization, combined with strong systems engineering skills to ship reliable AI capabilities outside the data center. The ideal candidate has shipped edge AI in production where compute, memory, energy, and connectivity constraints shape engineering trade-offs.

Required Qualifications - Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field - 6+ years of ML engineering experience with edge or mobile AI - Strong proficiency in Python and C++ - Hands-on experience with model compression, quantization, and pruning - Experience with at least one major edge inference framework - Solid understanding of mobile and embedded hardware architectures - Experience deploying ML models to production on mobile or embedded platforms - Strong performance engineering and profiling skills - Familiarity with on-device privacy and security considerations - Strong communication and cross-functional collaboration skills

Preferred Qualifications - Experience with custom NPU or DSP toolchains - Familiarity with federated learning or on-device personalizatio