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AI Engineer, Time-Series Signal Processing

BrightAI CorporationPalo Alto, CAEngineering
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Salary
Not listed
Job type
Full-time
Posted
8 Aug 2025
Status
Open · checked 7d ago

About this role

BrightAI Corporation is seeking an AI Engineer specializing in Time-Series Signal Processing to join the engineering team in Palo Alto, California. This role involves building cutting-edge artificial intelligence models to interpret high-frequency sensor data from physical infrastructure systems.

Role Overview

The AI Engineer – Time-Series Signal Processing will lead the development of machine learning solutions built on multi-modal sensor inputs. This position suits professionals with a background in digital signal processing and machine learning who want to build real-time AI models for noisy data streams at both the edge and cloud scale.

Key Responsibilities

Design and implement real-time signal processing and machine learning pipelines for multi-modal time-series data from sources like IMUs, microphones, pressure sensors, and ultrasonic transducers.
Develop and deploy models for time-series classification, prediction, anomaly detection, activity recognition, condition monitoring, and pattern analysis.
Research and implement recurrent neural networks, such as LSTMs and GRUs, alongside temporal transformer models.
Build, tune, and explain classical and tree-based machine learning models, including XGBoost, LightGBM, and Random Forests.
Ingest and model high-frequency, multi-channel operational data streams from physical assets using SCADA systems and industrial telemetry data.
Collaborate with hardware, embedded, and product teams to integrate models into edge devices and Internet of Things platforms.
Optimize signal-processing techniques like filtering, feature extraction, and event detection to improve model input quality.
Create and maintain scalable workflows for ingesting, labeling, training, and evaluating multi-channel time-series datasets.
Ensure production model robustness, performance, and reliability in edge deployments.

Requirements

Degree in Electrical Engineering, Computer Science, or a related field with a strong focus on signal processing, time-series analysis, and machine learning.
Minimum of 2 years of professional experience developing signal processing and machine learning solutions for time-series sensor data.
Demonstrated history of bringing at least one machine learning solution to market.
Deep understanding of digital signal processing methods, including filtering, sampling, windowing, and the Fast Fourier Transform.
Hands-on experience with recurrent neural networks or temporal convolutional networks for time-series modeling.
Proficiency with tree-based and gradient-boosting models applied to sensor data, including hyperparameter tuning and explainability.
Experience working with SCADA systems and industrial telemetry data, such as high-frequency sensor feeds and time-stamped operational data.
Proven experience handling time-series data from physical sensors like IMUs, microphones, and vibration or pressure sensors.
Strong programming abilities in Python and fluency with machine learning frameworks like PyTorch and TensorFlow.
Experience optimizing and deploying models in real-time or near-real-time environments, including edge devices or resource-constrained embedded systems.

Nice to Have

Experience building end-to-end artificial intelligence systems for structural health monitoring, condition monitoring, anomaly detection, activity recognition, or motion tracking.
Experience with predictive maintenance on industrial equipment utilizing SCADA or telemetry data.
Familiarity with experiment tracking and model lifecycle tooling such as MLflow and DVC.
Exposure to streaming and online inference patterns like exponentially weighted moving average normalization and windowed feature extraction on live data.
Proficiency in embedded software or deploying models to constrained environments using tools like TFLite or ONNX.
Familiarity with containerized workflows, Linux-based development environments, Agile workflows, JIRA, Git, and CI/CD pipelines.
Prior work history in startup or fast-paced teams building real-time systems from scratch.

Skills and Tools

Python
PyTorch
TensorFlow
Keras
XGBoost
LightGBM
Random Forests
Digital Signal Processing (DSP)
SCADA Systems and Industrial Telemetry
Edge and Cloud Deployment

About the Company

BrightAI Corporation is a high-growth Physical AI company that transforms how businesses interact with the physical world through intelligent automation. The company platform processes visual, spatial, and temporal data from billions of real-world events gathered via edge devices, mobile sensors, and large-scale cloud infrastructure to deliver real-time decisions.

How to Apply

Interested candidates should visit the official BrightAI company careers page to submit an application for this position.

Skills and tech stack

PythonPyTorchTensorFlow

Questions candidates ask

What is the primary focus of the AI Engineer role at BrightAI?

The role focuses on leading the development of AI and machine learning solutions built on high-frequency multi-modal sensor data, modeling and understanding time-series signals from IoT devices.

How many years of experience are required for this position?

Candidates must have at least 2+ years of experience developing signal processing and machine learning solutions for time-series sensor data.

What programming languages and frameworks are needed?

Strong coding skills in Python are required, along with fluency in machine learning and deep learning frameworks such as PyTorch, TensorFlow, and Keras.

Where is the job located?

The position is based in Palo Alto, California.

What domain experience is considered beneficial as a bonus?

Bonus qualifications include experience building end-to-end AI systems for structural health monitoring, predictive maintenance on industrial equipment, streaming inference patterns, and deploying models to constrained embedded environments.

Ready to apply?

The application is on the official BrightAI Corporation careers page.

Apply on company site