Embedded CV/ML Engineer

SGS Consulting; Sacramento (CA); Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

SGS Consulting seeks an experienced engineer to design and deploy high-performance computer vision and edge ML pipelines on resource-constrained hardware. You will optimize latency and throughput for multiple edge-AI features and integrate algorithms within the Android camera framework.

You will collaborate with hardware and software teams to bridge sensors with on-device NPUs, profiling memory, power, and timing to ensure real-time performance for biometric verification, image restoration, or

Formación

• Proficiency in Python and C/C++ for low-level software development and optimization.
• Familiarity with ML frameworks optimized for edge deployment.
• Solid understanding of computer vision fundamentals and camera architectures.
• Experience with real-time on-device processing and edge AI.
• Knowledge of Android camera framework and multimedia subsystems.

Responsabilidades

• Design and deploy high-performance computer vision and ML pipelines on resource-constrained edge hardware.
• Optimize concurrent ML workloads to maximize throughput and minimize latency.
• Integrate edge-AI algorithms within the Android camera framework and multimedia subsystems.
• Collaborate across software and hardware teams to bridge camera sensors with on-device NPUs.
• Profile and optimize memory footprint, power consumption, and execution timing to meet on-device constraints.

Conocimientos

Python

C/C++

Android platform

Edge ML

DSP

Camera architectures

Model optimization

Profiling tools

MAANG experience

Educación

Bachelor's degree in CS/EE/CE

Herramientas

TensorFlow Lite

ONNX Runtime

PyTorch Edge

Descripción del empleo

Job Responsibilities

Design and deploy high-performance computer vision and machine learning pipelines directly onto resource-constrained edge hardware.Optimize concurrent ML workloads to maximize throughput and minimize latency when running multiple edge-AI features simultaneously.Integrate edge-AI algorithms seamlessly within the Android camera framework and multimedia subsystems.Collaborate across software and hardware teams to bridge low-level camera sensor subsystems with on-device neural processing units (NPUs).Profile and optimize memory footprint, power consumption, and execution timing to meet strict on-device performance constraints.

Skills

Proficiency in Python, and C and C++ for low-level software development and optimization.Experience with machine learning frameworks optimized for edge deployment, such as TensorFlow Lite, ONNX Runtime, or PyTorch Edge.Familiarity with the Android platform stack, specifically regarding multimedia or camera subsystem integration.Solid understanding of computer vision fundamentals, digital signal processing (DSP), or basic camera architectures.Previous AI experience.Hands-on experience developing within the Android camera framework to control, process, route, and transform real-time image streams.Experience with model optimization techniques such as quantization, pruning, and hardware-specific compilation for NPUs, GPUs, or DSPs.Background in developing low-latency algorithms for real-time edge applications (e.g., biometric verification, image restoration, or on-device language processing).Familiarity with hardware-constrained vision pipelines, including specialized sensor integration and multi-threaded concurrency models.Hands-on experience debugging low-level software utilizing hardware profiling tools to isolate memory bottlenecks and scheduling conflicts.Former MAANG experience.

Education/Experience

Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.