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Trainee Time Series Analysis Jobs (NOW HIRING)

Ceribell, Inc

Data Scientist

Sunnyvale, CA

Use time-series analysis, statistical signal processing and machine learning techniques to design classification algorithms for various neurological indications * Analyze data for trends and patterns ...

M&T Bank

Model Risk Analyst-Validation

Buffalo, NY · On-site

$91K - $101K/yr

Data Science concepts, including statistics and probability, exploratory data analysis (EDA), machine learning, model evaluation and selection, feature engineering, time series analysis, loss ...

M&T Bank

Model Risk Analyst-Validation

Buffalo, NY · On-site

$91K - $101K/yr

Data Science concepts, including statistics and probability, exploratory data analysis (EDA), machine learning, model evaluation and selection, feature engineering, time series analysis, loss ...

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As of Jul 7, 2026, the average yearly pay for trainee time series analysis in the United States is $43,530.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,000.00 and $51,000.00 per year, depending on experience, location, and employer.
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Trainee Time Series Analysis jobs near you
Senior AI Engineer, Time-Series Signal Processing

Senior AI Engineer, Time-Series Signal Processing

BrightAI

Palo Alto, CA • On-site

$123K - $168K/yr

Full-time

Posted 23 days ago

Job description

Job Summary:
Bright.AI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation. They are seeking a Senior AI Engineer to lead the development of AI/ML solutions focused on modeling and understanding time-series signals from IoT devices. The role involves building real-time AI models and collaborating with various teams to integrate these models into physical infrastructure systems.
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.
• 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.
• Stay current with advances in time-series modeling, signal processing, and real-time inference, and incorporate them into product roadmaps.
• Ensure model robustness, performance, and reliability in production environments, including edge deployments.
Qualifications:
Required:
• M.S. or Ph.D. in Electrical Engineering, Computer Science, or a related field, with a strong focus on signal processing, time-series analysis, and machine learning.
• 5+ 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.
• Deep understanding of digital signal processing (DSP) methods: filtering, sampling, windowing, FFT, feature extraction, etc.
• Hands-on experience with RNNs (especially LSTMs/GRUs) and/or temporal convolutional networks for time-series modeling.
• Proven experience with time-series data from physical sensors such as IMUs, microphones, vibration or pressure sensors.
• Strong coding skills in Python and fluency with ML/DL frameworks (e.g., PyTorch, TensorFlow, Keras).
• Experience in optimizing and deploying models in real-time or near-real-time environments, including edge devices or resource-constrained embedded systems.
• Fluency with best practices in data labeling, augmentation, and evaluation for time-series tasks.
• Excellent problem-solving and collaboration skills with the ability to work across teams.
• Strong communication skills with the ability to convey findings and recommendations to internal and external stakeholders.
Preferred:
• Experience building end-to-end AI systems for structural health monitoring, condition monitoring, anomaly detection, activity recognition, or motion tracking.
• 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.
• Prior work in startup or high-pace teams with experience in building real-time systems from the ground up.
Company:
BrightAI provides physical AI solutions for infrastructure and services. Founded in 2020, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.
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About BrightAI

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

San Francisco, CA, US

Year founded

2019

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