Immediate need for a talented
Gaming - Embedded Software Engineer II. This is a
06+ Months Contract opportunity with long-term potential and is located in
Sunnyvale, CA (Hybrid). Please review the job description below and contact me ASAP if you are interested.
Job ID:26-30698
Pay Range: $80 - $85/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
Key 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.
Key Requirements and Technology Experience:- 5+ years of experience in embedded systems development with a strong background in C++, Python, and Embedded Systems with DSP.
- Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.
- Proficiency in Python, 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 Meta experience.
Our client is a leading
Social media Industry and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
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