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Embedded Software Engineer II
Job Location:
Job Location:
Sunnyvale, CA - USA
Hourly Salary:
USD 80 - 90
Hourly Salary:
Posted:
25 October 2026 (7 hours ago)
Posted:
Application Deadline:
22 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Title: Embedded Software Engineer
Location: Sunnyvale CA (Onsite 3 days)
Duration: 12 months
Responsibilities
Minimum Qualifications
Preferred Qualifications
Location: Sunnyvale CA (Onsite 3 days)
Duration: 12 months
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.
Minimum Qualifications
- Bachelors degree in Computer Science Electrical Engineering Computer Engineering or a related technical field or equivalent practical experience.
- 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
Preferred Qualifications
- 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.
Required Experience:
IC
