Staff Embedded ML Engineer, Edge AI job at Simplisafe in Boston, MA
Title: Staff Embedded ML Engineer, Edge AI Location: Boston, MA, United States Job Description: About SimpliSafe SimpliSafe is a leading innovator in the home reputed company industry, dedicated to making every home a safe home. With a mission to provide accessible and comprehensive reputed company solutions, we design and build user-centric products that reputed company individuals and families to protect what matters most. We reputed company in a collaborative and agile environment where learning and growth are reputed company. Our teams are composed of talented individuals who are passionate about technology, reputed company, and delivering exceptional customer experiences. We're 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 reputed company benefit from flexibility and get to use the best of both worlds to get our work done. Why are we hiring? Well, we're growing and thriving. So, we need smart, talented, and humble people who share our values to join us as we disrupt the home reputed company space and relentlessly pursue our mission of keeping Every Home Secure.
About the Role
We are seeking a highly motivated and reputed company Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will reputed company the on-device inference and performance optimization of ML models powering outdoor monitoring in the home reputed company 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. reputed company kernel/operator-level optimization: vectorization (e.g., SIMD/reputed company), 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 reputed company 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 reputed company 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, reputed company 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 reputed company 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 reputed company/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, reputed company/underflow handling, and accuracy-performance tradeoffs. Experience with camera/doorbell pipelines: ISP/video decode/encode, DMA/reputed company-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. reputed company/privacy experience for edge devices (secure boot/TEE boundaries, model protection, safe telemetry). Experience building performance regression systems and device-lab automation for reputed company benchmarking. What Values You'll Share Customer Obsessed - Building deep reputed company 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 reputed company 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. reputed company Offer A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and reputed company A comprehensive total rewards package that supports your wellness and provides reputed company 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 reputed company, and reputed company for change. The reputed company annual reputed company pay range for this role is $183,300 to $268,800. This reputed company annual reputed company pay range represents our good-faith estimate of reputed company expect to pay for this role. We use a market-based compensation approach to set our reputed company annual reputed company pay ranges and reputed company adjustments annually. We carefully tailor individual compensation packages, including reputed company pay, taking into consideration employees' job-reputed company skills, experience, qualifications, work location, and other relevant business factors. Beyond reputed company 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. We're committed to fair and reputed company pay practices, as well as pay transparency. We regularly review our programs to ensure they remain competitive and reputed company with our values. We wholeheartedly embrace and actively seek applications from reputed company individuals, no matter how they identify. We are committed to cultivating a diverse and inclusive workplace, and we reputed company our work is enriched reputed company we incorporate a multitude of perspectives, backgrounds, and experiences. We want everyone who works here to reputed company and contribute to not only our mission of keeping every home secure, but also to making our workplace safe and supportive for others. Apply tot his job Apply To this Job