BrightAI
AI Engineer, Time-Series Signal Processing
Palo Alto, CA · Senior
Sponsorship not specifiedDetected 5 days ago
PythonGitCloud PlatformsCI/CDLinuxMachine LearningTensorFlowPyTorchNLPA/B TestingJiraEmbedded SystemsElectrical EngineeringSignal ProcessingSensorsResearchCommunicationCollaborationProblem SolvingSCADA
About the role
- AI Engineer, Time-Series Signal Processing BrightAI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation.
Responsibilities
- Design and implement real-time signal processing and ML pipelines for multi-modal time-series data such as those acquired from IMUs, microphones, pressure or force sensors, ultrasonic transducers, and similar sensor sources.
- Develop and deploy ML models for time-series classification, prediction, anomaly detection, activity recognition, condition monitoring and pattern analysis.
- Lead research and implementation of RNN-based architectures (especially LSTMs and their variants) as well as temporal transformer models as needed.
- Build and tune classical and tree-based ML models (XGBoost, LightGBM, Random Forests, and other gradient-boosted ensembles) for time-series tasks, including feature engineering and model interpretability (e.g., SHAP).
- Collaborate with hardware, embedded, and product teams to integrate models into edge devices and IoT platforms.
- Drive experimentation and optimization of signal-processing techniques (e.g., filtering, feature extraction, event detection) to enhance model input quality.
- Design and maintain scalable workflows for ingesting, labeling, training, and evaluating multi-channel time-series datasets.
- Prior work in startup or high-pace teams with experience in building real-time systems from the ground up.
Requirements
- Required Skills & Expertise
- 2+ years of experience developing signal processing and ML solutions for time-series sensor data.
- Track record of bringing at least one ML solution to market.
- Hands-on experience with RNNs (especially LSTMs/GRUs) and/or temporal convolutional networks for time-series modeling.
- Proficiency with tree-based and gradient-boosting models (XGBoost, LightGBM, Random Forests) applied to time-series and sensor data, including hyperparameter tuning and explainability.
- Proven experience with time-series data from physical sensors such as IMUs, microphones, vibration or pressure sensors.
Nice to have
- Experience with predictive maintenance on industrial equipment using SCADA/telemetry data.
- Familiarity with experiment tracking and model lifecycle tooling (e.g., MLflow, DVC).
- Exposure to streaming/online inference patterns (e.g., EWMA normalization, windowed feature extraction on live data).
- Proficiency in embedded software or deploying models to constrained environments (e.g., using TFLite, ONNX, or custom firmware).
- Familiarity with containerized workflows and Linux-based development environments.
- Experience with Agile workflows and tools such as JIRA, Git, and CI/CD pipelines.
Skills
- AI Engineer, Time-Series Signal Processing
- BrightAI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation.
Benefits
- Experience building end-to-end AI systems for structural health monitoring, condition monitoring, anomaly detection, activity recognition, or motion tracking.
- Educational Background
- Degree in Electrical Engineering, Computer Science, or a related field, with a strong focus on signal processing, time-series analysis, and machine learning.
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This listing is sourced directly from BrightAI's careers page and normalized into a canonical job model.