8 days ago
Sunnyvale, CA, USAStaff+
Base Salary
$227k - $300k/yr
Responsibilities
- Build and train Edge AI models, including Transformers, LLMs, CNNs, LSTMs, and tree-based models, for logs, traces, and multimodal data.
- Integrate machine learning flows with Gemini, OpenAI, and Claude APIs and create synthetic data.
- Develop clustering and anomaly-detection algorithms to identify log patterns, software regressions, race conditions, crash precursors, and sensor anomalies.
- Design supervised and unsupervised models for time-series data from CAN buses and onboard sensors.
- Correlate signal anomalies across modalities with system events to identify root causes.
- Port and optimize PyTorch and TensorFlow models for CPU, GPU, and embedded NPU targets.
- Apply quantization, pruning, distillation, and memory optimization for strict RAM and Flash constraints.
- Define on-device data filtering and determine which data is processed locally versus in the cloud.
- Lead the Edge ML pipeline architecture and mentor junior engineers.
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, Software Engineering, or a related field.
- 10+ years of Machine Learning Engineering experience, including 3+ years focused on Edge AI or Embedded Systems.
- Proven experience mentoring junior software engineers.
- Expert Python skills and working knowledge of modern C++, including C++14/17 for inference.
- Deep proficiency with PyTorch or TensorFlow and experience with ONNX, TFLite, or TVM.
- Experience with NLP, textual data parsing, sequence modeling, vector stores, or lightweight LLMs/SLMs.
- Experience with scikit-learn, tslearn, or statsmodels for sensor-data anomaly detection.
- Ability to lead technical projects from concept to production and communicate trade-offs with stakeholders.
- Experience deploying to ARM-based Edge environments, manually managing memory, and working with limited compute resources.
- Strong Computer Vision or ADAS experience is encouraged.
- A master’s or PhD in Computer Science, Engineering, or a related field is preferred.
- Familiarity with automotive formats and systems such as CAN, DBC, UDS, SOME/IP, or MQTT is preferred.
- Understanding of Linux/QNX kernel logs, process states, and OS-level debugging is preferred.
- Experience with NVIDIA TensorRT or Qualcomm SNPE is preferred.
Benefits
- Medical, dental, and vision coverage.
- Flexible and Dependent Care Expense program.
- 401(k) retirement plan.
- Basic, voluntary, and AD&D life insurance.
- Unlimited paid time off and 14+ paid holidays.
- Hybrid work arrangement in Sunnyvale, with three days per week in the office.
- Complimentary lunches, snacks, and beverages on onsite workdays.
- Wellness benefit allowance.
- Phone and internet reimbursement.
- Computer accessory allowance.
