Senior Staff Machine Learning Engineer
WeAreDevelopers
$227k - $300k/yr Employer stated
Found 1 week ago · Confirmed live 1 week ago
Skills this job asks for
- Edge AI
- Memory Management
- ONNX
- TensorFlow
- TensorRT
- Anomaly Detection
- Embedded Systems
- Inference Engines
- Python
- PyTorch
- QNX
- scikit-learn
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At a glance
- Type
- Full-time
- Level
- Senior
- Experience
- 10+ years
- Work model
- Not stated
- Schedule
- Not stated
- Education
- Bachelor's degree
- Benefits
- Not stated
- Team
- Engineering
Description
Back Senior Staff Machine Learning Engineer Sonatus, Inc San Jose, CA, United States 1 day ago Discuss this with your agent Open in Claude Open in ChatGPT Copy prompt Apply on the employer's site Prepare application Draft this with your agent Open in Claude Open in ChatGPT Copy prompt Role details Contract type Permanent contract Employment type Full-time (> 32 hours) Experience level Expert Experience required 3 years minimum Compensation $227,000.0 - $300,000.0 Working hours Regular working hours Job source the employer's site Tech stack Adobe Flash Artificial Intelligence Computer Vision C++ (Programming Language) CAN Bus Software Code Optimization Software Debugging Linux Python (Programming Language) Machine Learning Message Queuing Telemetry Transport (MQTT) Natural Language Processing +20 more OpenAI Tensorflow Software Engineering Supervised Learning Pytorch Large Language Models Data Strategy Discretization Scikit Learn Information Technology Statistics Packages ONNX (Open Neural Network Exchange) Format Autoencoders Reasoning Engines TensorRT Multiaccess Edge Computing Claude Google Gemini C++14 Recurrent Neural Networks Job description Build and train AI Edge models (e.g., Transformers, LLMs, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities. Integrate ML flows, including cloud-based LLM APIs (Gemini, OpenAI, Claude), with emphasis on synthetic data creation. Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors. Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors. Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes. Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs. Apply quantization, pruning, distillation, and memory optimization to ensure models run within strict RAM/Flash budgets. Define the data strategy for on-device filtering: pre-processing on device and decide which data is processed locally versus processed in the cloud. Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI. Requirements Bachelor’s degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. 10+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems. Proven experience mentoring junior engineers in software development. Expert Python (for training) and decent working knowledge of modern C++ (C++14/17 for inference). Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM. Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector stores, or lightweight LLMs/SLMs. Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data. Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment. Ability to communicate with stakeholders and articulate trade-offs. Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. Candidates with a strong Computer Vision (CV) / ADAS track record are highly encouraged to apply! Desired Skills: MS/PhD in Computer Science, Engineering, or related fields. Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT. Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. Experience with NVIDIA TensorRT, Qualcomm SNPE. Benefits & conditions Sunnyvale HQ Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Hybrid office work arrangement Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus (“Company”) could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,000-$300,000 USD About the company At Sonatus, we’re driving the transformation to AI-enabled softwar
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