AI Engineer, Time-Series Signal Processing
BrightAI Corporation10 days ago
Palo Alto, CA, USAMid Level
Responsibilities
- Design and implement real-time signal-processing and ML pipelines for multimodal time-series sensor data.
- Develop and deploy models for time-series classification, prediction, anomaly detection, activity recognition, condition monitoring, and pattern analysis.
- Research and implement RNN-based, LSTM, GRU, and temporal transformer architectures.
- Build and tune XGBoost, LightGBM, Random Forest, and other gradient-boosted models with feature engineering and interpretability analysis.
- Ingest and model high-frequency SCADA and industrial telemetry data from physical assets.
- Collaborate with hardware, embedded, and product teams to integrate models into edge devices and IoT platforms.
- Optimize filtering, feature extraction, event detection, and other signal-processing techniques.
- Maintain workflows for labeling, training, and evaluating multichannel time-series datasets.
- Ensure model robustness, performance, and reliability in production and edge deployments.
Requirements
- A degree in Electrical Engineering, Computer Science, or a related field with focus on signal processing, time-series analysis, and machine learning.
- At least 2 years of experience developing signal-processing and ML solutions for time-series sensor data.
- Experience bringing at least one ML solution to market.
- Deep knowledge of digital signal processing, including filtering, sampling, windowing, FFT, and feature extraction.
- Hands-on experience with RNNs, LSTMs, GRUs, or temporal convolutional networks.
- Proficiency with tree-based and gradient-boosting models, including XGBoost, LightGBM, and Random Forests.
- Experience with SCADA systems, industrial telemetry, and high-frequency multichannel sensor feeds.
- Experience working with physical sensor data such as IMU, microphone, vibration, or pressure data.
- Strong Python skills and fluency with ML/DL frameworks such as PyTorch, TensorFlow, or Keras.
- Experience optimizing and deploying models for real-time or near-real-time inference on edge or resource-constrained devices.
- Knowledge of time-series data labeling, augmentation, and evaluation practices.
- Strong problem-solving, collaboration, and communication skills.
- Bonus experience with structural health monitoring, predictive maintenance, experiment tracking, streaming inference, embedded deployment, containerized workflows, Linux, startup environments, JIRA, Git, or CI/CD pipelines.
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About BrightAI Corporation
BrightAI is transforming essential services with Physical AI—real-world intelligence that drives proactive, data-driven operations. Built on the Stateful platform, BrightAI empowers operators of critical infrastructure to collect and connect sensor data in real time, uncover hidden insights, and make smarter decisions. From predictive diagnostics and autonomous robotics to digital twins and AI-enabled workflows, BrightAI solutions serve industries including water, power, gas compression, pest control, HVAC, and manufacturing. By turning complex physical signals into actionable intelligence, BrightAI is redefining how essential services are delivered and sustained.