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Staff CV Applied Research Engineer, Edge AI

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SimpliSafe

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Location:
United States , Boston

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

183300.00 - 268800.00 USD / Year
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Job Description:

We are seeking a highly motivated and experienced Computer Vision Applied Research Engineer to join our growing Edge AI team. As a key contributor, you will lead development of on-device machine learning for outdoor monitoring in the home security space. You will build and optimize computer vision models that run in real time on resource-constrained embedded devices like outdoor cameras and doorbell cameras, balancing accuracy with latency, memory, power, and reliability in challenging conditions (night, weather, motion blur, occlusions).

Job Responsibility:

  • Lead end-to-end development of edge ML models for outdoor monitoring (e.g., person/vehicle/package detection, classification, tracking, segmentation, event understanding)
  • Architect, train, and deploy transformer-based vision models (e.g., compact ViTs, hierarchical transformers, DETR-style detectors) and hybrid CNN-transformer backbones optimized for embedded inference
  • Drive model efficiency through resource-aware design and training, including: Architecture: Token/patch reduction, efficient attention variants, early-exit / conditional compute
  • Training: distillation from large transformer teachers to edge students
  • Compression: Quantization (PTQ/QAT), pruning, mixed precision, and operator-aware optimization
  • Translate product requirements into model targets (accuracy, FPS, memory footprint, power/thermal) and ensure models meet budgets on doorbell/outdoor camera hardware
  • Partner with embedded/firmware and platform teams to integrate models into production pipelines
  • profile bottlenecks and improve end-to-end runtime performance
  • Define evaluation strategies tailored to outdoor edge deployments
  • perform failure analysis and improve long-tail robustness (nighttime, rain/snow, backlight, fast motion)
  • Set technical direction and raise engineering standards: best practices for experimentation, reproducibility, model/version management, and deployment readiness
  • mentor other ML engineers

Requirements:

  • 8+ years in applied ML/ML engineering, including shipping production CV models
  • Strong computer vision background with deep learning expertise across detection/classification/segmentation/tracking
  • Hands-on experience with vision transformers and/or DETR-style architectures, including practical knowledge of efficiency trade-offs for edge deployment
  • Demonstrated success deploying models in resource-constrained, real-time environments (embedded/mobile/IoT/edge)
  • Deep experience in model optimization: QAT/PTQ, distillation, pruning, compression, mixed precision, and hardware/runtime-aware training
  • Proficiency in Python and PyTorch and/or TensorFlow
  • ability to productionize models and collaborate with systems engineers (C++ experience strongly preferred)
  • Staff-level leadership: ability to drive ambiguous initiatives, align stakeholders, and mentor engineers

Nice to have:

  • Expertise in efficient transformer techniques (e.g., attention approximations, windowed/local attention, KV caching where applicable, token merging, sparsity) and their deployment implications
  • Experience building model “ladders” across multiple chipsets/device tiers with consistent KPIs and automated regression testing
  • Experience with embedded inference tooling and runtimes (e.g., TFLite, ONNX Runtime, TensorRT) and model export/compatibility constraints
  • Familiarity with embedded accelerators and profiling (ARM NEON, DSP/NPU toolchains), kernel/operator tuning, and real-time video pipelines
  • Experience with long-tail data strategies (active learning, hard-negative mining) and edge reliability/telemetry feedback loops
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
  • 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
  • Participation in our annual bonus program, equity, and other forms of compensation, in addition to a full range of medical, retirement, and lifestyle benefits

Additional Information:

Job Posted:
March 04, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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