Staff Embedded ML Engineer, Edge AI

About SimpliSafe

Were a high-tech home security company thats passionate about protecting the life youve built and our mission of keeping Every Home Secure. And weve created a culture here that cares just as deeply about the career youre building. Ours is a no ego culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of all those who we protect. We dont just want you to work here. We want you to grow and thrive here.

Were embracing a hybrid work model that enables our teams to split their time between office and home. Hybrid for us means we expect our teams to come together in our state-of-the-art office on two core days typically Tuesday Wednesday or Thursday working together in person and choosing where they work for the remainder of the week. We all benefit from flexibility and get to use the best of both worlds to get our work done.

Why are we hiring

Well were growing and thriving. So we need smart talented and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure.

About the Role

We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor you will lead the on-device inference and performance optimization of ML models powering outdoor monitoring in the home security space. This role is less about inventing new CV architectures and more about making models fast power-efficient stable and shippable on real embedded hardware (outdoor cameras and doorbells). You will operate across the stack (from model runtime integration down to kernel/operator optimization memory movement scheduling and accelerator utilization) to deliver reliable real-time behavior under tight compute memory bandwidth and thermal constraints across device tiers.

Responsibilities:

• Own the embedded deployment and performance of on-device ML inference for outdoor monitoring workloads (real-time video/event pipelines).
• Optimize end-to-end inference performance across CPU/DSP/NPU/GPU (as applicable): latency throughput (FPS) memory footprint power thermals startup time and stability.
• Perform kernel/operator-level optimization:
• vectorization (e.g. SIMD/NEON) tiling cache-friendly memory layouts
• reducing bandwidth and memory copies optimizing post-processing
• fusing ops minimizing synchronization/overhead thread scheduling
• Integrate and maintain ML models within embedded pipelines:
• model import/export validation operator compatibility graph transforms
• runtime integration in C/C (including pre/post-processing)
• robust error handling watchdogs and safe fallback behavior
• Drive quantization and deployment readiness from an embedded perspective:
• validate INT8/FP16 paths calibration flows numerical accuracy checks
• debug quantization edge cases and operator mismatches on target runtimes
• Build tooling for profiling benchmarking and regression tracking on devices:
• per-layer timing memory tracking thermal/perf tests CI gating
• automated performance regression gating across device tiers and firmware versions
• Partner closely with ML engineers to translate model changes into deployment impact; provide constraints and design guidance that improve deployability and performance.
• Provide Staff-level leadership: set performance standards lead technical reviews mentor engineers and influence platform roadmap for on-device ML.

Qualifications:

• 8 years of experience in embedded systems and/or performance engineering with experience shipping production software on constrained devices.
• Strong C/C expertise with deep knowledge of low-level performance topics: CPU architecture memory hierarchy concurrency and real-time considerations.
• Demonstrated experience optimizing ML inference on embedded targets including operator/kernel tuning and end-to-end pipeline optimization.
• Familiarity with modern vision model families (transformer-based detectors such as DEIM/DFINE/RT-DETR series and CNN-based detectors such as YOLO family or similar) sufficient to optimize their execution characteristics (tensor shapes attention/conv patterns post-processing).
• Experience with on-device inference runtimes and deployment workflows (e.g. TFLite ONNX Runtime TensorRT or vendor runtimes) including operator support constraints and graph-level transformations.
• Strong debugging and profiling skills (perf flame graphs hardware counters tracing) and ability to drive performance investigations to closure.
• Ability to lead cross-functionally across ML firmware and hardware teams; comfortable defining benchmarks/KPIs and making tradeoffs.

Bonus Points:

• Experience with embedded accelerators and vendor toolchains (DSP/NPU compilers delegates GPU compute custom runtimes).
• SIMD expertise (ARM NEON/SVE) hand-tuned kernels or experience with libraries like XNNPACK/QNNPACK/oneDNN/CMSIS-NN (or equivalents).
• Experience with quantized inference (INT8) at scale: calibration strategies numerical debugging overflow/underflow handling and accuracy-performance tradeoffs.
• Experience with camera/doorbell pipelines: ISP/video decode/encode DMA/zero-copy buffers multi-threaded real-time streaming.
• Exposure to OS/firmware constraints (embedded Linux RTOS) power management thermal throttling behavior and performance under sustained load.
• Security/privacy experience for edge devices (secure boot/TEE boundaries model protection safe telemetry).
• Experience building performance regression systems and device-lab automation for continuous benchmarking.

What Values Youll Share

• Customer Obsessed - Building deep empathy for our customers putting them at the core of our work and developing strong long-term relationships with them.
• Aim High - Always challenging ourselves and others to raise the bar.
• No Ego - Maintaining a no job too small attitude and an open inclusive and humble style.
• One Team - Taking a highly collaborative approach to achieving success.
• Lift As We Climb - Investing in developing others and helping others around us succeed.
• Lean & Nimble - Working with agility and efficiency to experiment in an often ambiguous environment.

What We Offer

• A mission- and values-driven culture and a safe inclusive environment where you can build grow and thrive
• A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families (For more information on our total rewards please click here)
• Free SimpliSafe system and professional monitoring for your home.
• Employee Resource Groups (ERGs) that bring people together give opportunities to network mentor and develop and advocate for change.

The target annual base pay range for this role is $185500 to $244600

This target annual base pay range represents our good-faith estimate of what we expect to pay for this role. We use a market-based compensation approach to set our target annual base pay ranges and make adjustments annually. We carefully tailor individual compensation packages including base pay taking into consideration employees job-related skills experience qualifications work location and other relevant business factors.

Beyond base pay we offer a Total Rewards package that may include participation in our annual bonus program equity and other forms of compensation in addition to a full range of medical retirement and lifestyle benefits. More details can befound here.

Were committed to fair and equitable pay practices as well as pay transparency. We regularly review our programs to ensure they remain competitive and aligned with our values.

We wholeheartedly embrace and actively seek applications from all individuals no matter how they identify. We are committed to cultivating a diverse and inclusive workplace and we believe our work is enriched when we incorporate a multitude of perspectives backgrounds and experiences. We want everyone who works here to thrive and contribute to not only our mission of keeping every home secure but also to making our workplace safe and supportive for others. If a reasonable accommodation may be needed to fully participate in the job application or interview process to perform the essential functions of a position or to receive other benefits and privileges of employment please contact.