In this role, you will:
- Optimize and accelerate ML models for embedded hardware using techniques such as quantization, pruning, knowledge distillation, model compression, and hardware-specific optimizations
- Develop high-performance custom kernels using CUDA, OpenCL, or other low-level programming tools to accelerate computations and implement efficient algorithms
- Leverage and customize inference optimization frameworks like TensorRT, TVM, or ONNX Runtime to maximize performance on target platforms
- Profile and analyze model performance, identify bottlenecks, and implement solutions to improve computational efficiency and reduce latency
- Collaborate with cross-functional teams, including hardware engineers and software developers, to co-design software and hardware solutions that maximize overall system performance.
Qualifications:
- BS, MS, or PhD with academic or at least 2-3 years of industry experience in optimizing and accelerating machine learning models for embedded systems
- You are a skilled software engineer with experience in Python, C++, CUDA programming, and strong problem-solving skills
- You are passionate about pushing the boundaries of ML performance on hardware and have ideally worked on embedded platforms or autonomous systems before
- You also have a strong knowledge of low-level kernel development and experience with ML optimization techniques such as quantization, pruning, model compression, and knowledge distillation
What we offer:
- Competitive compensation package including equity and biannual bonuses
- Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Anthem, and Guardian (including a medical plan with infertility benefits)Flexible PTO and generous parental leave policies
- Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
- Long Term Disability, Short Term Disability, Life Insurance
- Wellbeing Benefits - Headspace, One Medical, Gympass, Spring Health
- Fidelity 401(k)Commuter, FSA, Dependent Care FSA, HSA
- Various incentive programs (referral bonuses, patent bonuses, etc.)
0 applies
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