Job Description
A Senior Machine Learning Engineer responsible for designing, optimizing, and deploying computer vision and multimodal ML models on constrained edge platforms for Samsara's in-vehicle safety and driver experience systems, contributing to real-time perception and safety improvements across global IoT deployments.
Key Responsibilities
- Design, optimize, and deploy computer vision and multimodal ML models for edge platforms in in-vehicle camera systems
- Apply model optimization techniques such as quantization, pruning, and distillation for real-time inference under hardware constraints
- Collaborate with research and product teams to translate AI detections into deployable edge models
- Develop benchmarking, profiling, and validation frameworks to ensure model robustness across deployed devices
- Improve and maintain the edge ML toolchain, advocating best practices in model optimization and deployment
Requirements
- Minimum of 5 years of experience developing and deploying deep learning models for edge, embedded, or real-time systems.
- Strong background in computer vision or multimodal machine learning, such as 2D/3D CNNs or Transformers, using industry-standard deep learning frameworks.
- Proficiency in Python and C++, with hands-on experience optimizing inference runtimes and applying model optimization techniques for edge deployment.
- Deep understanding of performance tuning, including compiler- or DSP-level optimizations, runtime profiling, latency analysis, and memory management on constrained hardware.
- Familiarity with middleware or streaming frameworks used in real-time perception pipelines.
- Excellent cross-functional communication and collaboration skills, especially across machine learning, firmware, and product domains.
- Experience bringing machine learning infrastructure or runtime systems from prototype to production at scale.
- Background in multimodal machine learning, such as audio-vision fusion or event-based detection systems.
- Experience validating AI models across large, diverse fleets of deployed devices in real-world environments.
Benefits & Perks
Competitive total compensation package including base salary, bonus, and equity (RSUs)
Remote and flexible working options
Health benefits
Employee-led remote work support
Opportunities for career growth and learning
Inclusive work environment with accommodations for disabilities
Ready to Apply?
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